nohup: ignoring input
Please build and install Nvidia apex package with option '--cuda_ext' according to https://github.com/NVIDIA/apex#from-source .
model_name qformer_v3_bib_q_instruct_QAprompt_mm_reloadbert_full_0.7719
model_base /mnt/data_nas/luyt/VLM_weight/Bunny-v1_0-3B/
Loading Bunny from base model...
load model path directly..... and model_name.lower() qformer_v3_bib_q_instruct_qaprompt_mm_reloadbert_full_0.7719
load vision_tower from pretrained......
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.embeddings.patch_embedding.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.embeddings.patch_embedding.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.embeddings.position_embedding.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.0.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.1.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.2.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.3.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.4.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.5.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.6.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.7.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.8.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.9.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.10.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.11.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.12.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.13.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.14.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.15.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.16.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.17.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.18.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.19.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.20.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.21.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.22.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.23.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.24.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.25.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.k_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.k_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.v_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.v_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.q_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.q_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.self_attn.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.layer_norm1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.layer_norm1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.layer_norm2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.encoder.layers.26.layer_norm2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.post_layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.post_layernorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.probe: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.attention.in_proj_weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.attention.in_proj_bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.attention.out_proj.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.attention.out_proj.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.layernorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.layernorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.mlp.fc1.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.mlp.fc1.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.mlp.fc2.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for vision_model.head.mlp.fc2.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
torch.Size([2560, 1152])
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.embeddings.word_embeddings.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.embeddings.position_embeddings.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.embeddings.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.embeddings.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.attention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.intermediate.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.intermediate.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for cls.predictions.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for cls.predictions.transform.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for cls.predictions.transform.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for cls.predictions.transform.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for cls.predictions.transform.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
Loading pretrained qformer weights...
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.0.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.1.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.2.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.3.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.4.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.5.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.6.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.7.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.8.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.9.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.query.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.query.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.key.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.key.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.value.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.self.value.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.output.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.output.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.output.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.crossattention.output.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.10.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.intermediate_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.intermediate_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output_query.dense.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output_query.dense.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output_query.LayerNorm.weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bert.encoder.layer.11.output_query.LayerNorm.bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
load vlm_att_encoder from pretrained <All keys matched successfully>
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for weight: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
/home/pai/lib/python3.11/site-packages/torch/nn/modules/module.py:2025: UserWarning: for bias: copying from a non-meta parameter in the checkpoint to a meta parameter in the current model, which is a no-op. (Did you mean to pass `assign=True` to assign items in the state dictionary to their corresponding key in the module instead of copying them in place?)
  warnings.warn(f'for {key}: copying from a non-meta parameter in the checkpoint to a meta '
load vlm_att_ln from pretrained <All keys matched successfully>

Loading checkpoint shards:   0%|                                                                | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards:  50%|████████████████████████████                            | 1/2 [00:03<00:03,  3.61s/it]
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████| 2/2 [00:04<00:00,  1.89s/it]
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████| 2/2 [00:04<00:00,  2.15s/it]
BunnyQformer_v3_bib_PhiForCausalLM(
  (model): BunnyQformer_v3_bib_PhiModel(
    (embed_tokens): Embedding(50295, 2560, padding_idx=50256)
    (embed_dropout): Dropout(p=0.0, inplace=False)
    (layers): ModuleList(
      (0-31): 32 x PhiDecoderLayer(
        (self_attn): PhiAttention(
          (q_proj): Linear(in_features=2560, out_features=2560, bias=True)
          (k_proj): Linear(in_features=2560, out_features=2560, bias=True)
          (v_proj): Linear(in_features=2560, out_features=2560, bias=True)
          (dense): Linear(in_features=2560, out_features=2560, bias=True)
          (rotary_emb): PhiRotaryEmbedding()
        )
        (mlp): PhiMLP(
          (activation_fn): NewGELUActivation()
          (fc1): Linear(in_features=2560, out_features=10240, bias=True)
          (fc2): Linear(in_features=10240, out_features=2560, bias=True)
        )
        (input_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)
        (resid_dropout): Dropout(p=0.1, inplace=False)
      )
    )
    (final_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)
    (vision_tower): SigLipVisionTower(
      (vision_tower): SigLipVisionModel(
        (vision_model): SigLipVisionTransformer(
          (embeddings): SigLipVisionEmbeddings(
            (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
            (position_embedding): Embedding(729, 1152)
          )
          (encoder): SigLipEncoder(
            (layers): ModuleList(
              (0-25): 26 x SigLipEncoderLayer(
                (self_attn): SigLipAttention(
                  (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
                  (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
                  (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
                  (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
                )
                (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
                (mlp): SigLipMLP(
                  (activation_fn): PytorchGELUTanh()
                  (fc1): Linear(in_features=1152, out_features=4304, bias=True)
                  (fc2): Linear(in_features=4304, out_features=1152, bias=True)
                )
                (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
              )
            )
          )
          (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
          (head): Identity()
        )
      )
    )
    (mm_projector): Sequential(
      (0): Linear(in_features=1152, out_features=2560, bias=True)
      (1): GELU(approximate='none')
      (2): Linear(in_features=2560, out_features=2560, bias=True)
    )
    (vlm_att_ln): LayerNorm((1408,), eps=1e-05, elementwise_affine=True)
    (vlm_att_encoder): BertLMHeadModel(
      (bert): BertModel(
        (embeddings): BertEmbeddings(
          (word_embeddings): Embedding(30523, 768)
          (position_embeddings): Embedding(512, 768)
          (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
          (dropout): Dropout(p=0.1, inplace=False)
        )
        (encoder): BertEncoder(
          (layer): ModuleList(
            (0): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (1): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (2): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (3): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (4): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (5): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (6): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (7): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (8): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (9): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (10): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (crossattention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=1408, out_features=768, bias=True)
                  (value): Linear(in_features=1408, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (11): BertLayer(
              (attention): BertAttention(
                (self): BertSelfAttention(
                  (query): Linear(in_features=768, out_features=768, bias=True)
                  (key): Linear(in_features=768, out_features=768, bias=True)
                  (value): Linear(in_features=768, out_features=768, bias=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
                (output): BertSelfOutput(
                  (dense): Linear(in_features=768, out_features=768, bias=True)
                  (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                  (dropout): Dropout(p=0.1, inplace=False)
                )
              )
              (intermediate): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (intermediate_query): BertIntermediate(
                (dense): Linear(in_features=768, out_features=3072, bias=True)
                (intermediate_act_fn): GELUActivation()
              )
              (output_query): BertOutput(
                (dense): Linear(in_features=3072, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
          )
        )
      )
      (cls): None
    )
    (vlm_att_projector): Linear(in_features=1152, out_features=1408, bias=True)
    (vlm_att_deprojector): Linear(in_features=768, out_features=1152, bias=True)
    (vlm_cross_attn): vlm_cross_attn(
      (self_attn): MultiheadAttention(
        (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
      )
      (linear1): Linear(in_features=2304, out_features=2048, bias=True)
      (dropout): Dropout(p=0.1, inplace=False)
      (linear2): Linear(in_features=2048, out_features=1, bias=True)
      (norm1): LayerNorm((2304,), eps=1e-05, elementwise_affine=True)
      (norm2): LayerNorm((1152,), eps=1e-05, elementwise_affine=True)
      (dropout1): Dropout(p=0.1, inplace=False)
      (dropout2): Dropout(p=0.1, inplace=False)
    )
  )
  (lm_head): Linear(in_features=2560, out_features=50295, bias=False)
)
Loading stage2 weights...
non_lora_trainables.bin of previous stage exits
load additional weight from previous stage: []
Loading LoRA weights from previous stage...
Merging stage2 weights...
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'model.vlm_att_encoder.bert.encoder.layer.11.attention.self.key.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.self.key.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.self.value.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.self.value.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.output.dense.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.output.dense.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.output.LayerNorm.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.attention.output.LayerNorm.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.intermediate.dense.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.intermediate.dense.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.output.dense.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.output.dense.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.output.LayerNorm.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.output.LayerNorm.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.intermediate_query.dense.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.intermediate_query.dense.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.output_query.dense.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.output_query.dense.bias', 'model.vlm_att_encoder.bert.encoder.layer.11.output_query.LayerNorm.weight', 'model.vlm_att_encoder.bert.encoder.layer.11.output_query.LayerNorm.bias', 'model.vlm_att_projector.weight', 'model.vlm_att_projector.bias', 'model.vlm_att_deprojector.weight', 'model.vlm_att_deprojector.bias', 'model.vlm_cross_attn.self_attn.in_proj_weight', 'model.vlm_cross_attn.self_attn.in_proj_bias', 'model.vlm_cross_attn.self_attn.out_proj.weight', 'model.vlm_cross_attn.self_attn.out_proj.bias', 'model.vlm_cross_attn.linear1.weight', 'model.vlm_cross_attn.linear1.bias', 'model.vlm_cross_attn.linear2.weight', 'model.vlm_cross_attn.linear2.bias', 'model.vlm_cross_attn.norm1.weight', 'model.vlm_cross_attn.norm1.bias', 'model.vlm_cross_attn.norm2.weight', 'model.vlm_cross_attn.norm2.bias'])
[]

  0%|                                                                                        | 0/1495 [00:00<?, ?it/s]prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity of the building?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity of the building?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.

/home/pai/lib/python3.11/site-packages/transformers/generation/configuration_utils.py:492: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.
  warnings.warn(
prompts: [["How is the image clarity of the building?\nA. Blurry\nB. Clear\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

  0%|                                                                                | 1/1495 [00:00<24:30,  1.02it/s]
[Running Accuracy]: 0.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1:   0%| | 1/1495 [00:00<24
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity of the building?\nA. Blurry\nB. Clear\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the human is cropped out of the image?
A. His hand
B. His head
C. His leg
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the human is cropped out of the image?
A. His hand
B. His head
C. His leg
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the human is cropped out of the image?\nA. His hand\nB. His head\nC. His leg\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1:   0%| | 2/1495 [00:01<14
[Running Accuracy]: 0.5000,[Response]: B.<|endoftext|>, [Correct Ans]: His head, , [Prog]: 2:   0%| | 2/1495 [00:01<14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the human is cropped out of the image?\nA. His hand\nB. His head\nC. His leg\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in this image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in this image?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.5000,[Response]: B.<|endoftext|>, [Correct Ans]: His head, , [Prog]: 2:   0%| | 3/1495 [00:01<11
[Running Accuracy]: 0.6667,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 3:   0%| | 3/1495 [00:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.6667,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 3:   0%| | 4/1495 [00:
[Running Accuracy]: 0.7500,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 4:   0%| | 4/1495 [00:01<10:11, 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the feet of the bird blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the feet of the bird blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the feet of the bird blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7500,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 4:   0%| | 5/1495 [00:02<09:27, 
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 5:   0%| | 5/1495 [00:02<09:27, 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the feet of the bird blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this imag clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this imag clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this imag clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 5:   0%| | 6/1495 [00:02<08:51, 
[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 6:   0%| | 6/1495 [00:02<08:51, 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this imag clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness does the background skyscrapers of this image have?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blurriness does the background skyscrapers of this image have?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness does the background skyscrapers of this image have?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 6:   0%| | 7/1495 [00:02<08:37, 
[Running Accuracy]: 0.7143,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 7:   0%| | 7/1495 [00:02<08:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness does the background skyscrapers of this image have?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in the image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Out of Focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion occurs in the image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Out of Focus
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion occurs in the image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\nD. Out of Focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7143,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 7:   1%| | 8/1495 [00:03<08:1
[Running Accuracy]: 0.7500,[Response]: D.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 8:   1%| | 8/1495 [00:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in the image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\nD. Out of Focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the electric pole clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the electric pole clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the electric pole clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7500,[Response]: D.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 8:   1%| | 9/1495 [00:0
[Running Accuracy]: 0.6667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 9:   1%| | 9/1495 [00:03<08:08, 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the electric pole clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any problem with image compression distortion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any problem with image compression distortion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any problem with image compression distortion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.6667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 9:   1%| | 10/1495 [00:03<08:09,
[Running Accuracy]: 0.7000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 10:   1%| | 10/1495 [00:03<08:09,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any problem with image compression distortion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 10:   1%| | 11/1495 [00:04<08:13,
[Running Accuracy]: 0.6364,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 11:   1%| | 11/1495 [00:04<08:13
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the vehicle in the image?
A. A little bit blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the vehicle in the image?
A. A little bit blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the vehicle in the image?\nA. A little bit blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.6364,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 11:   1%| | 12/1495 [00:04<08:07
[Running Accuracy]: 0.6667,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 12:   1%| | 12/1495 [00:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the vehicle in the image?\nA. A little bit blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.6667,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 12:   1%| | 13/1495 [00:
[Running Accuracy]: 0.6923,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 13:   1%| | 13/1495 [00:04<07:58
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.6923,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 13:   1%| | 14/1495 [00:05<08:00
[Running Accuracy]: 0.7143,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 14:   1%| | 14/1495 [00:05<08:00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7143,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 14:   1%| | 15/1495 [00:05<07:42
[Running Accuracy]: 0.7333,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 15:   1%| | 15/1495 [00:05<07:42
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the motion blur of the car in this image?
A. Weak
B. Medium
C. Strong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the motion blur of the car in this image?
A. Weak
B. Medium
C. Strong
Answer with the option's letter from the given choices directly.

prompts: [["How is the motion blur of the car in this image?\nA. Weak\nB. Medium\nC. Strong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7333,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 15:   1%| | 16/1495 [00:05<09:12
[Running Accuracy]: 0.7500,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 16:   1%| | 16/1495 [00:05<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the motion blur of the car in this image?\nA. Weak\nB. Medium\nC. Strong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7500,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 16:   1%| | 17/1495 [00:06<08
[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 17:   1%| | 17/1495 [00:06<08:41,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat's fur clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat's fur clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat's fur clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 17:   1%| | 18/1495 [00:06<08:14,
[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 18:   1%| | 18/1495 [00:06<08:14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat's fur clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the fire hydrant in the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the fire hydrant in the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the fire hydrant in the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 18:   1%| | 19/1495 [00:06<07:46
[Running Accuracy]: 0.7895,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 19:   1%| | 19/1495 [00:06<07:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the fire hydrant in the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the shoes take center stage in the composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the shoes take center stage in the composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Do the shoes take center stage in the composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7895,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 19:   1%| | 20/1495 [00:07<07:5
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 20:   1%| | 20/1495 [00:07<07:50
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the shoes take center stage in the composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness level of this starry sky?
A. High
B. Average
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness level of this starry sky?
A. High
B. Average
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness level of this starry sky?\nA. High\nB. Average\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 20:   1%| | 21/1495 [00:07<07:47
[Running Accuracy]: 0.8095,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 21:   1%| | 21/1495 [00:07<07:47
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness level of this starry sky?\nA. High\nB. Average\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?
A. Vibrant
B. Dark
C. Fresh
D. Plain
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual impression does the image give?
A. Vibrant
B. Dark
C. Fresh
D. Plain
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does the image give?\nA. Vibrant\nB. Dark\nC. Fresh\nD. Plain\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8095,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 21:   1%| | 22/1495 [00:07<07:43
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 22:   1%| | 22/1495 [00:07<07:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?\nA. Vibrant\nB. Dark\nC. Fresh\nD. Plain\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this image?
A. Normal
B. Dim
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this image?
A. Normal
B. Dim
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this image?\nA. Normal\nB. Dim\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 22:   2%| | 23/1495 [00:08<09:4
[Running Accuracy]: 0.8261,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 23:   2%| | 23/1495 [00:08<09:43
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this image?\nA. Normal\nB. Dim\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8261,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 23:   2%| | 24/1495 [00:08<08:48
[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 24:   2%| | 24/1495 [00:08<08:48,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?
A. house
B. runway
C. lawn
D. airplane
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, which object is emphasized in the center?
A. house
B. runway
C. lawn
D. airplane
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, which object is emphasized in the center?\nA. house\nB. runway\nC. lawn\nD. airplane\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 24:   2%| | 25/1495 [00:08<08:09,
[Running Accuracy]: 0.8400,[Response]: D.<|endoftext|>, [Correct Ans]: airplane, , [Prog]: 25:   2%| | 25/1495 [00:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?\nA. house\nB. runway\nC. lawn\nD. airplane\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the greenery in this image?
A. Medium
B. Very poor
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the greenery in this image?
A. Medium
B. Very poor
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the greenery in this image?\nA. Medium\nB. Very poor\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8400,[Response]: D.<|endoftext|>, [Correct Ans]: airplane, , [Prog]: 25:   2%| | 26/1495 [00:09<
[Running Accuracy]: 0.8462,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 26:   2%| | 26/1495 [00:09<07:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the greenery in this image?\nA. Medium\nB. Very poor\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8462,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 26:   2%| | 27/1495 [00:09<07:3
[Running Accuracy]: 0.8519,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 27:   2%| | 27/1495 [00:09<07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant object in the image?
A. Architectural steps
B. Architectural pillars
C. Woman's hair
D. Woman's clothing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most vibrant object in the image?
A. Architectural steps
B. Architectural pillars
C. Woman's hair
D. Woman's clothing
Answer with the option's letter from the given choices directly.

prompts: [["What is the most vibrant object in the image?\nA. Architectural steps\nB. Architectural pillars\nC. Woman's hair\nD. Woman's clothing\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8519,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 27:   2%| | 28/1495 [00:09<07:4
[Running Accuracy]: 0.8571,[Response]: D.<|endoftext|>, [Correct Ans]: Woman's clothing, , [Prog]: 28:   2%| | 28/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant object in the image?\nA. Architectural steps\nB. Architectural pillars\nC. Woman's hair\nD. Woman's clothing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person highlighted as the main subject?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person highlighted as the main subject?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the person highlighted as the main subject?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8571,[Response]: D.<|endoftext|>, [Correct Ans]: Woman's clothing, , [Prog]: 28:   2%| | 29/1495
[Running Accuracy]: 0.8621,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 29:   2%| | 29/1495 [00:10<07:39
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person highlighted as the main subject?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8621,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 29:   2%| | 30/1495 [00:10<09:28
[Running Accuracy]: 0.8667,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 30:   2%| | 30/1495 [00:10<09:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the humans in this image?
A. Noise
B. Blur
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the humans in this image?
A. Noise
B. Blur
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the humans in this image?\nA. Noise\nB. Blur\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8667,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 30:   2%| | 31/1495 [00:10<08:3
[Running Accuracy]: 0.8387,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 31:   2%| | 31/1495 [00:10<08:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the humans in this image?\nA. Noise\nB. Blur\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. Red car
B. Building
C. Ground
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. Red car
B. Building
C. Ground
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. Red car\nB. Building\nC. Ground\nD. Sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8387,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 31:   2%| | 32/1495 [00:11<08:0
[Running Accuracy]: 0.8438,[Response]: A.<|endoftext|>, [Correct Ans]: Red car, , [Prog]: 32:   2%| | 32/1495 [00:11<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. Red car\nB. Building\nC. Ground\nD. Sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus of the umbrella in this image?
A. Good
B. Poor
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus of the umbrella in this image?
A. Good
B. Poor
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus of the umbrella in this image?\nA. Good\nB. Poor\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8438,[Response]: A.<|endoftext|>, [Correct Ans]: Red car, , [Prog]: 32:   2%| | 33/1495 [00:11<0
[Running Accuracy]: 0.8485,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 33:   2%| | 33/1495 [00:11<07:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus of the umbrella in this image?\nA. Good\nB. Poor\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there motion blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there motion blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8485,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 33:   2%| | 34/1495 [00:11<07:2
[Running Accuracy]: 0.8529,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 34:   2%| | 34/1495 [00:11<07:25
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8529,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 34:   2%| | 35/1495 [00:12<08:39
[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 35:   2%| | 35/1495 [00:12<08:39,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of this image?
A. Yellow
B. Red
C. Blue
D. Green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of this image?
A. Yellow
B. Red
C. Blue
D. Green
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of this image?\nA. Yellow\nB. Red\nC. Blue\nD. Green\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 35:   2%| | 36/1495 [00:12<08:10,
[Running Accuracy]: 0.8611,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 36:   2%| | 36/1495 [00:12<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of this image?\nA. Yellow\nB. Red\nC. Blue\nD. Green\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background forest in the image?
A. Moderate
B. Serious
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background forest in the image?
A. Moderate
B. Serious
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background forest in the image?\nA. Moderate\nB. Serious\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8611,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 36:   2%| | 37/1495 [00:12<08:
[Running Accuracy]: 0.8649,[Response]: B.<|endoftext|>, [Correct Ans]: Serious, , [Prog]: 37:   2%| | 37/1495 [00:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background forest in the image?\nA. Moderate\nB. Serious\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8649,[Response]: B.<|endoftext|>, [Correct Ans]: Serious, , [Prog]: 37:   3%| | 38/1495 [00:13<0
[Running Accuracy]: 0.8684,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 38:   3%| | 38/1495 [00:13<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is your feeling on this image?
A. Neutral
B. Pleasant
C. Annoying
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is your feeling on this image?
A. Neutral
B. Pleasant
C. Annoying
Answer with the option's letter from the given choices directly.

prompts: [["How is your feeling on this image?\nA. Neutral\nB. Pleasant\nC. Annoying\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8684,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 38:   3%| | 39/1495 [00:13<07
[Running Accuracy]: 0.8718,[Response]: C.<|endoftext|>, [Correct Ans]: Annoying, , [Prog]: 39:   3%| | 39/1495 [00:13<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is your feeling on this image?\nA. Neutral\nB. Pleasant\nC. Annoying\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Yellow
B. Green
C. Red
D. White
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Yellow
B. Green
C. Red
D. White
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Yellow\nB. Green\nC. Red\nD. White\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8718,[Response]: C.<|endoftext|>, [Correct Ans]: Annoying, , [Prog]: 39:   3%| | 40/1495 [00:13<
[Running Accuracy]: 0.8750,[Response]: B.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 40:   3%| | 40/1495 [00:13<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Yellow\nB. Green\nC. Red\nD. White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8750,[Response]: B.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 40:   3%| | 41/1495 [00:14<07:
[Running Accuracy]: 0.8537,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 41:   3%| | 41/1495 [00:14<07:02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?
A. Dynamic
B. Gloomy
C. Terrific
D. Cheerful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the feeling of this image?
A. Dynamic
B. Gloomy
C. Terrific
D. Cheerful
Answer with the option's letter from the given choices directly.

prompts: [["How is the feeling of this image?\nA. Dynamic\nB. Gloomy\nC. Terrific\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8537,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 41:   3%| | 42/1495 [00:14<07:11
[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 42:   3%| | 42/1495 [00:14<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?\nA. Dynamic\nB. Gloomy\nC. Terrific\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Fair
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Fair
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Fair\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 42:   3%| | 43/1495 [00:14<08
[Running Accuracy]: 0.8605,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 43:   3%| | 43/1495 [00:14<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Fair\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the cat in this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the cat in this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the cat in this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8605,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 43:   3%| | 44/1495 [00:15<08:
[Running Accuracy]: 0.8636,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 44:   3%| | 44/1495 [00:15<08:15
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the cat in this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in this image?
A. Noise
B. Compression Artifacts
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion occurs in this image?
A. Noise
B. Compression Artifacts
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion occurs in this image?\nA. Noise\nB. Compression Artifacts\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8636,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 44:   3%| | 45/1495 [00:15<10:20
[Running Accuracy]: 0.8667,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 45:   3%| | 45/1495 [00:15<10:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in this image?\nA. Noise\nB. Compression Artifacts\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which hand of the person is clear in focus?
A. Right hand
B. Left hand
C. No hand
D. Both hand
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which hand of the person is clear in focus?
A. Right hand
B. Left hand
C. No hand
D. Both hand
Answer with the option's letter from the given choices directly.

prompts: [["Which hand of the person is clear in focus?\nA. Right hand\nB. Left hand\nC. No hand\nD. Both hand\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8667,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 45:   3%| | 46/1495 [00:16<09:2
[Running Accuracy]: 0.8478,[Response]: B.<|endoftext|>, [Correct Ans]: Right hand, , [Prog]: 46:   3%| | 46/1495 [00:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which hand of the person is clear in focus?\nA. Right hand\nB. Left hand\nC. No hand\nD. Both hand\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?
A. Poor
B. Acceptable
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Poor
B. Acceptable
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Poor\nB. Acceptable\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8478,[Response]: B.<|endoftext|>, [Correct Ans]: Right hand, , [Prog]: 46:   3%| | 47/1495 [00:1
[Running Accuracy]: 0.8511,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 47:   3%| | 47/1495 [00:16<08:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?\nA. Poor\nB. Acceptable\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?
A. Bad
B. Good
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Bad
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Bad\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8511,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 47:   3%| | 48/1495 [00:16<09:5
[Running Accuracy]: 0.8542,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 48:   3%| | 48/1495 [00:16<09:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?\nA. Bad\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8542,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 48:   3%| | 49/1495 [00:17<09:1
[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 49:   3%| | 49/1495 [00:17<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the man's clothes in the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the man's clothes in the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the man's clothes in the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 49:   3%| | 50/1495 [00:17<
[Running Accuracy]: 0.8600,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 50:   3%| | 50/1495 [00:17<08:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the man's clothes in the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the brightest parts of the image two people?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the brightest parts of the image two people?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the brightest parts of the image two people?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8600,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 50:   3%| | 51/1495 [00:17<08:1
[Running Accuracy]: 0.8627,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 51:   3%| | 51/1495 [00:17<08:17,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the brightest parts of the image two people?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture real or AI generated?
A. real
B. AI generated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture real or AI generated?
A. real
B. AI generated
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture real or AI generated?\nA. real\nB. AI generated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8627,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 51:   3%| | 52/1495 [00:18<07:56,
[Running Accuracy]: 0.8654,[Response]: B.<|endoftext|>, [Correct Ans]: AI generated, , [Prog]: 52:   3%| | 52/1495 [00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture real or AI generated?\nA. real\nB. AI generated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bird in the picture hanging on the wall clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bird in the picture hanging on the wall clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bird in the picture hanging on the wall clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8654,[Response]: B.<|endoftext|>, [Correct Ans]: AI generated, , [Prog]: 52:   4%| | 53/1495 [00
[Running Accuracy]: 0.8679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 53:   4%| | 53/1495 [00:18<07:40
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bird in the picture hanging on the wall clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 53:   4%| | 54/1495 [00:18<07:21
[Running Accuracy]: 0.8704,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 54:   4%| | 54/1495 [00:18<07:21
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion does the grassland in the image suffer from?
A. Noise
B. Underexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion does the grassland in the image suffer from?
A. Noise
B. Underexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion does the grassland in the image suffer from?\nA. Noise\nB. Underexposure\nC. Motion Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8704,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 54:   4%| | 55/1495 [00:19<09:11
[Running Accuracy]: 0.8727,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 55:   4%| | 55/1495 [00:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion does the grassland in the image suffer from?\nA. Noise\nB. Underexposure\nC. Motion Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman in red clothes emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman in red clothes emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman in red clothes emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8727,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 55:   4%| | 56/1495 [00:
[Running Accuracy]: 0.8750,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 56:   4%| | 56/1495 [00:19<08:24
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman in red clothes emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest part of this image?
A. Tree branch
B. Sky
C. Building
D. Grassland
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the darkest part of this image?
A. Tree branch
B. Sky
C. Building
D. Grassland
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest part of this image?\nA. Tree branch\nB. Sky\nC. Building\nD. Grassland\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8750,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 56:   4%| | 57/1495 [00:19<07:57
[Running Accuracy]: 0.8596,[Response]: D.<|endoftext|>, [Correct Ans]: Tree branch, , [Prog]: 57:   4%| | 57/1495 [00:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest part of this image?\nA. Tree branch\nB. Sky\nC. Building\nD. Grassland\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image contain any background bokeh to highlight the subject?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image contain any background bokeh to highlight the subject?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image contain any background bokeh to highlight the subject?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8596,[Response]: D.<|endoftext|>, [Correct Ans]: Tree branch, , [Prog]: 57:   4%| | 58/1495 [00:
[Running Accuracy]: 0.8448,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 58:   4%| | 58/1495 [00:20<07:33,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image contain any background bokeh to highlight the subject?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8448,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 58:   4%| | 59/1495 [00:20<09:11,
[Running Accuracy]: 0.8475,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 59:   4%| | 59/1495 [00:20<09:11
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Rate the photogragh aesthetics of the image.
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Rate the photogragh aesthetics of the image.
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["Rate the photogragh aesthetics of the image.\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8475,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 59:   4%| | 60/1495 [00:20<08:23
[Running Accuracy]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 60:   4%| | 60/1495 [00:20<08:23
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Rate the photogragh aesthetics of the image.\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Overexposure
B. Motion blur
C. Underexposure
D. Brightness
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Overexposure
B. Motion blur
C. Underexposure
D. Brightness
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Brightness\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B

[Running Accuracy]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 60:   4%| | 61/1495 [00:21<09:47
[Running Accuracy]: 0.8525,[Response]: B<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 61:   4%| | 61/1495 [00:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Brightness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this image?
A. Average
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this image?
A. Average
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this image?\nA. Average\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8525,[Response]: B<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 61:   4%| | 62/1495 [00:2
[Running Accuracy]: 0.8548,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 62:   4%| | 62/1495 [00:22<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this image?\nA. Average\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry due to movement?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurry due to movement?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurry due to movement?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8548,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 62:   4%| | 63/1495 [00:22<
[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 63:   4%| | 63/1495 [00:22<09:57
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry due to movement?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the singing man in the image emphasized in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the singing man in the image emphasized in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the singing man in the image emphasized in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 63:   4%| | 64/1495 [00:22<09:21
[Running Accuracy]: 0.8594,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 64:   4%| | 64/1495 [00:22<09:21
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the singing man in the image emphasized in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the goldfish in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the goldfish in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the goldfish in the image?\nA. Clear\nB. Medium\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8594,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 64:   4%| | 65/1495 [00:23<09:04
[Running Accuracy]: 0.8462,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 65:   4%| | 65/1495 [00:23<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the goldfish in the image?\nA. Clear\nB. Medium\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8462,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 65:   4%| | 66/1495 [00:23<08
[Running Accuracy]: 0.8485,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 66:   4%| | 66/1495 [00:23<08:28
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the picture is significantly affected by motion blur?
A. Narrow track
B. Pole
C. Wide track
D. Grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the picture is significantly affected by motion blur?
A. Narrow track
B. Pole
C. Wide track
D. Grass
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the picture is significantly affected by motion blur?\nA. Narrow track\nB. Pole\nC. Wide track\nD. Grass\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8485,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 66:   4%| | 67/1495 [00:23<07:55
[Running Accuracy]: 0.8507,[Response]: C.<|endoftext|>, [Correct Ans]: Wide track, , [Prog]: 67:   4%| | 67/1495 [00:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the picture is significantly affected by motion blur?\nA. Narrow track\nB. Pole\nC. Wide track\nD. Grass\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness contrast in this image?
A. High
B. Fair
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness contrast in this image?
A. High
B. Fair
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness contrast in this image?\nA. High\nB. Fair\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8507,[Response]: C.<|endoftext|>, [Correct Ans]: Wide track, , [Prog]: 67:   5%| | 68/1495 [00:2
[Running Accuracy]: 0.8382,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 68:   5%| | 68/1495 [00:23<07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness contrast in this image?\nA. High\nB. Fair\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the fire hydrant in this picture?
A. Fair
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the fire hydrant in this picture?
A. Fair
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the fire hydrant in this picture?\nA. Fair\nB. Clear\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8382,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 68:   5%| | 69/1495 [00:24<09:1
[Running Accuracy]: 0.8406,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 69:   5%| | 69/1495 [00:24<09:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the fire hydrant in this picture?\nA. Fair\nB. Clear\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What objects in this picture suffer underexposure the most?
A. Building
B. Sea
C. Trees
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What objects in this picture suffer underexposure the most?
A. Building
B. Sea
C. Trees
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["What objects in this picture suffer underexposure the most?\nA. Building\nB. Sea\nC. Trees\nD. Sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8406,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 69:   5%| | 70/1495 [00:25<13:
[Running Accuracy]: 0.8429,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 70:   5%| | 70/1495 [00:25<13:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What objects in this picture suffer underexposure the most?\nA. Building\nB. Sea\nC. Trees\nD. Sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image rich?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image rich?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image rich?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8429,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 70:   5%| | 71/1495 [00:25<11:
[Running Accuracy]: 0.8451,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 71:   5%| | 71/1495 [00:25<11:18
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image rich?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the largest flower in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the largest flower in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the largest flower in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8451,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 71:   5%| | 72/1495 [00:25<09:53
[Running Accuracy]: 0.8472,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 72:   5%| | 72/1495 [00:25<09:53
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the largest flower in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality problems exist in the image?
A. Blurred
B. Motion blur
C. Noise
D. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality problems exist in the image?
A. Blurred
B. Motion blur
C. Noise
D. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality problems exist in the image?\nA. Blurred\nB. Motion blur\nC. Noise\nD. Underexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8472,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 72:   5%| | 73/1495 [00:26<08:57
[Running Accuracy]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: Blurred, , [Prog]: 73:   5%| | 73/1495 [00:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality problems exist in the image?\nA. Blurred\nB. Motion blur\nC. Noise\nD. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the young person in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the young person in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the young person in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: Blurred, , [Prog]: 73:   5%| | 74/1495 [00:26<0
[Running Accuracy]: 0.8514,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 74:   5%| | 74/1495 [00:26<08:10
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the young person in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which person's face is the clearest in the image?
A. The person on the right
B. The man on the left
C. The man in the middle
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which person's face is the clearest in the image?
A. The person on the right
B. The man on the left
C. The man in the middle
Answer with the option's letter from the given choices directly.

prompts: [["Which person's face is the clearest in the image?\nA. The person on the right\nB. The man on the left\nC. The man in the middle\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8514,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 74:   5%| | 75/1495 [00:26<07:44
[Running Accuracy]: 0.8533,[Response]: B.<|endoftext|>, [Correct Ans]: The man on the left, , [Prog]: 75:   5%| | 75/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which person's face is the clearest in the image?\nA. The person on the right\nB. The man on the left\nC. The man in the middle\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the background suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the background suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the background suffer from over-exposure?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8533,[Response]: B.<|endoftext|>, [Correct Ans]: The man on the left, , [Prog]: 75:   5%| | 76/1
[Running Accuracy]: 0.8553,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 76:   5%| | 76/1495 [00:27<09:08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the background suffer from over-exposure?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the background in this image?
A. Bright
B. Average
C. Gloomy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the background in this image?
A. Bright
B. Average
C. Gloomy
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the background in this image?\nA. Bright\nB. Average\nC. Gloomy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8553,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 76:   5%| | 77/1495 [00:27<08:45
[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 77:   5%| | 77/1495 [00:27<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the background in this image?\nA. Bright\nB. Average\nC. Gloomy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the most eye-catching in the image?
A. Black
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the most eye-catching in the image?
A. Black
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the most eye-catching in the image?\nA. Black\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 77:   5%| | 78/1495 [00:27<08
[Running Accuracy]: 0.8590,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 78:   5%| | 78/1495 [00:27<08:07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the most eye-catching in the image?\nA. Black\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of image quality problem exists in the image?
A. Noise
B. Motion blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of image quality problem exists in the image?
A. Noise
B. Motion blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of image quality problem exists in the image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8590,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 78:   5%| | 79/1495 [00:28<07:40
[Running Accuracy]: 0.8481,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 79:   5%| | 79/1495 [00:28<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of image quality problem exists in the image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the bicycle in the image?
A. Somewhat blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the bicycle in the image?
A. Somewhat blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the bicycle in the image?\nA. Somewhat blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8481,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 79:   5%| | 80/1495 [00:28<07:
[Running Accuracy]: 0.8375,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 80:   5%| | 80/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the bicycle in the image?\nA. Somewhat blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is clear, without motion blurs?
A. The trees
B. The head of the children
C. The ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is clear, without motion blurs?
A. The trees
B. The head of the children
C. The ground
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is clear, without motion blurs?\nA. The trees\nB. The head of the children\nC. The ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8375,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 80:   5%| | 81/149
[Running Accuracy]: 0.8272,[Response]: C.<|endoftext|>, [Correct Ans]: The head of the children, , [Prog]: 81:   5%| |
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is clear, without motion blurs?\nA. The trees\nB. The head of the children\nC. The ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8272,[Response]: C.<|endoftext|>, [Correct Ans]: The head of the children, , [Prog]: 81:   5%| |
[Running Accuracy]: 0.8293,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 82:   5%| | 82/1495 [00:29<08:08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?
A. Over-exposure
B. Under-exposure
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of this image?
A. Over-exposure
B. Under-exposure
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of this image?\nA. Over-exposure\nB. Under-exposure\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8293,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 82:   6%| | 83/1495 [00:29<08:00
[Running Accuracy]: 0.8313,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 83:   6%| | 83/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?\nA. Over-exposure\nB. Under-exposure\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dominant color in the image green?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dominant color in the image green?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the dominant color in the image green?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8313,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 83:   6%| | 84/1495 [
[Running Accuracy]: 0.8214,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 84:   6%| | 84/1495 [00:29<07:37,
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dominant color in the image green?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there motion blur in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there motion blur in this photo?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8214,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 84:   6%| | 85/1495 [00:30<07:22,
[Running Accuracy]: 0.8235,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 85:   6%| | 85/1495 [00:30<07:22
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in this photo?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8235,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 85:   6%| | 86/1495 [00:30<07:29
[Running Accuracy]: 0.8256,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 86:   6%| | 86/1495 [00:30<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8256,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 86:   6%| | 87/1495 [00:31<09
[Running Accuracy]: 0.8276,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 87:   6%| | 87/1495 [00:31<09:45
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have an overexposure issue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have an overexposure issue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have an overexposure issue?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8276,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 87:   6%| | 88/1495 [00:31<09:09
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 88:   6%| | 88/1495 [00:31<09:09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have an overexposure issue?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there compression distortion in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there compression distortion in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there compression distortion in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 88:   6%| | 89/1495 [00:31<08:20
[Running Accuracy]: 0.8090,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 89:   6%| | 89/1495 [00:31<08:20
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there compression distortion in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of this photo high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clarity of this photo high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the clarity of this photo high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8090,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 89:   6%| | 90/1495 [00:32<07:54
[Running Accuracy]: 0.8111,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 90:   6%| | 90/1495 [00:32<07:54
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of this photo high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8111,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 90:   6%| | 91/1495 [00:32<11:57
[Running Accuracy]: 0.8132,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 91:   6%| | 91/1495 [00:32<11:57
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the small objects placed on the shelf in this image?
A. Vibrant
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the small objects placed on the shelf in this image?
A. Vibrant
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the small objects placed on the shelf in this image?\nA. Vibrant\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8132,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 91:   6%| | 92/1495 [00:33<10:23
[Running Accuracy]: 0.8152,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 92:   6%| | 92/1495 [00:33<1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the small objects placed on the shelf in this image?\nA. Vibrant\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?
A. Low
B. Clear
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Low
B. Clear
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Low\nB. Clear\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8152,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 92:   6%| | 93/1495 [00:33<0
[Running Accuracy]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 93:   6%| | 93/1495 [00:33<09:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?\nA. Low\nB. Clear\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Clear\nB. Blurry\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 93:   6%| | 94/1495 [00:33<08:
[Running Accuracy]: 0.8085,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 94:   6%| | 94/1495 [00:33<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Clear\nB. Blurry\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness does the sink in this image have?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blurriness does the sink in this image have?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness does the sink in this image have?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8085,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 94:   6%| | 95/1495 [00:34<0
[Running Accuracy]: 0.8105,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 95:   6%| | 95/1495 [00:34<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness does the sink in this image have?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of people arranged in this photo?
A. Monotonous
B. Vibrant
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of people arranged in this photo?
A. Monotonous
B. Vibrant
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of people arranged in this photo?\nA. Monotonous\nB. Vibrant\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8105,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 95:   6%| | 96/1495 [00:34<07
[Running Accuracy]: 0.8125,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 96:   6%| | 96/1495 [00:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of people arranged in this photo?\nA. Monotonous\nB. Vibrant\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8125,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 96:   6%| | 97/1495 [00:34<0
[Running Accuracy]: 0.8144,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 97:   6%| | 97/1495 [00:34<07:22
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8144,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 97:   7%| | 98/1495 [00:35<07:26
[Running Accuracy]: 0.8163,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 98:   7%| | 98/1495 [00:35<07:26
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise on the wall in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise on the wall in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8163,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 98:   7%| | 99/1495 [00:35<07:23
[Running Accuracy]: 0.8081,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 99:   7%| | 99/1495 [00:35<07:23
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this photo is severely affected by motion blur?
A. The ground
B. The tall building
C. The sky
D. The trees next to the fence
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this photo is severely affected by motion blur?
A. The ground
B. The tall building
C. The sky
D. The trees next to the fence
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this photo is severely affected by motion blur?\nA. The ground\nB. The tall building\nC. The sky\nD. The trees next to the fence\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8081,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 99:   7%| | 100/1495 [00:35<07:2
[Running Accuracy]: 0.8100,[Response]: D.<|endoftext|>, [Correct Ans]: The trees next to the fence, , [Prog]: 100:   7
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this photo is severely affected by motion blur?\nA. The ground\nB. The tall building\nC. The sky\nD. The trees next to the fence\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8100,[Response]: D.<|endoftext|>, [Correct Ans]: The trees next to the fence, , [Prog]: 100:   7
[Running Accuracy]: 0.8020,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 101:   7%| | 101/1495 [00:35<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image adopt a symmetrical composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image adopt a symmetrical composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image adopt a symmetrical composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8020,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 101:   7%| | 102/1495 [00:36<06:
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 102:   7%| | 102/1495 [00:36<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image adopt a symmetrical composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the skeleton very clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the skeleton very clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the skeleton very clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 102:   7%| | 103/1495 [00:36<06:
[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 103:   7%| | 103/1495 [00:36<06:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the skeleton very clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 103:   7%| | 104/1495 [00:36<06:4
[Running Accuracy]: 0.7981,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 104:   7%| | 104/1495 [00:36<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?
A. Intermediate
B. Faded
C. Saturated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the image?
A. Intermediate
B. Faded
C. Saturated
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the image?\nA. Intermediate\nB. Faded\nC. Saturated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7981,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 104:   7%| | 105/1495 [00:37<
[Running Accuracy]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 105:   7%| | 105/1495 [00:37<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?\nA. Intermediate\nB. Faded\nC. Saturated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Somewhat blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Somewhat blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 105:   7%| | 106/1495 [00:37<0
[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 106:   7%| | 106/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the cars in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the cars in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the cars in focus in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 106:   7%| | 107/149
[Running Accuracy]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 107:   7%| | 107/1495 [00:38<09:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the cars in focus in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 107:   7%| | 108/1495 [00:38<08:5
[Running Accuracy]: 0.7963,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 108:   7%| | 108/1495 [00:38<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?
A. Bee
B. Tree
C. Dandelion
D. Railing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Bee
B. Tree
C. Dandelion
D. Railing
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Bee\nB. Tree\nC. Dandelion\nD. Railing\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7963,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 108:   7%| | 109/1495 [00:38<08:
[Running Accuracy]: 0.7982,[Response]: C.<|endoftext|>, [Correct Ans]: Dandelion, , [Prog]: 109:   7%| | 109/1495 [00:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?\nA. Bee\nB. Tree\nC. Dandelion\nD. Railing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the balloon blown by the girl in this magazine bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the balloon blown by the girl in this magazine bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the balloon blown by the girl in this magazine bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7982,[Response]: C.<|endoftext|>, [Correct Ans]: Dandelion, , [Prog]: 109:   7%| | 110/1495 [00:
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 110:   7%| | 110/1495 [00:39<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the balloon blown by the girl in this magazine bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this picture?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this picture?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this picture?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 110:   7%| | 111/1495 [00:39<09:
[Running Accuracy]: 0.8018,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 111:   7%| | 111/1495 [00:39<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this picture?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8018,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 111:   7%| | 112/1495 [00:40<08
[Running Accuracy]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 112:   7%| | 112/1495 [00:40<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the women symmetric in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the women symmetric in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the women symmetric in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 112:   8%| | 113/1495 [00:40<07:
[Running Accuracy]: 0.7965,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 113:   8%| | 113/1495 [00:40<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the women symmetric in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is affected by slight motion blur?
A. Other pedestrians
B. Woman riding a bike
C. Vegetation
D. Building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is affected by slight motion blur?
A. Other pedestrians
B. Woman riding a bike
C. Vegetation
D. Building
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is affected by slight motion blur?\nA. Other pedestrians\nB. Woman riding a bike\nC. Vegetation\nD. Building\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7965,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 113:   8%| | 114/1495 [00:40<07:
[Running Accuracy]: 0.7982,[Response]: B.<|endoftext|>, [Correct Ans]: Woman riding a bike, , [Prog]: 114:   8%| | 114
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is affected by slight motion blur?\nA. Other pedestrians\nB. Woman riding a bike\nC. Vegetation\nD. Building\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the egret clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the egret clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the egret clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7982,[Response]: B.<|endoftext|>, [Correct Ans]: Woman riding a bike, , [Prog]: 114:   8%| | 115
[Running Accuracy]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 115:   8%| | 115/1495 [00:40<07:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the egret clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is obstructed by a dark object?
A. The top part
B. The right part
C. The bottom part
D. The left part
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is obstructed by a dark object?
A. The top part
B. The right part
C. The bottom part
D. The left part
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is obstructed by a dark object?\nA. The top part\nB. The right part\nC. The bottom part\nD. The left part\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 115:   8%| | 116/1495 [00:41<08:4
[Running Accuracy]: 0.7931,[Response]: B.<|endoftext|>, [Correct Ans]: The right part, , [Prog]: 116:   8%| | 116/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is obstructed by a dark object?\nA. The top part\nB. The right part\nC. The bottom part\nD. The left part\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?
A. Bright
B. Dim
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Bright
B. Dim
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. Bright\nB. Dim\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7931,[Response]: B.<|endoftext|>, [Correct Ans]: The right part, , [Prog]: 116:   8%| | 117/1495
[Running Accuracy]: 0.7863,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 117:   8%| | 117/1495 [00:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?\nA. Bright\nB. Dim\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two black cows in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two black cows in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the two black cows in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7863,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 117:   8%| | 118/1495 [00:4
[Running Accuracy]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 118:   8%| | 118/1495 [00:42<07:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two black cows in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 118:   8%| | 119/1495 [00:42<07:2
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 119:   8%| | 119/1495 [00:42<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 119:   8%| | 120/1495 [00:42<
[Running Accuracy]: 0.7833,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 120:   8%| | 120/1495 [00:42<07:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have a clear and distinctive subject?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have a clear and distinctive subject?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have a clear and distinctive subject?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7833,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 120:   8%| | 121/1495 [00:43<09:2
[Running Accuracy]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 121:   8%| | 121/1495 [00:43<09:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have a clear and distinctive subject?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 121:   8%| | 122/1495 [00:43<10:1
[Running Accuracy]: 0.7869,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 122:   8%| | 122/1495 [00:43<10:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7869,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 122:   8%| | 123/1495 [00:44<09:1
[Running Accuracy]: 0.7886,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 123:   8%| | 123/1495 [00:44<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers clearer or the leaves?
A. Leaves
B. Flowers
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers clearer or the leaves?
A. Leaves
B. Flowers
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers clearer or the leaves?\nA. Leaves\nB. Flowers\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7886,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 123:   8%| | 124/1495 [00:44<08
[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Flowers, , [Prog]: 124:   8%| | 124/1495 [00:44
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers clearer or the leaves?\nA. Leaves\nB. Flowers\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Flowers, , [Prog]: 124:   8%| | 125/1495 [00:44
[Running Accuracy]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 125:   8%| | 125/1495 [00:44<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 125:   8%| | 126/1495 [00:44<07:
[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 126:   8%| | 126/1495 [00:44<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual experience?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a refreshing visual experience?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing visual experience?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 126:   8%| | 127/1495 [00:45<07:
[Running Accuracy]: 0.7953,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 127:   8%| | 127/1495 [00:45<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual experience?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?
A. Black
B. White
C. Denim blue
D. Warm yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone in the image?
A. Black
B. White
C. Denim blue
D. Warm yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone in the image?\nA. Black\nB. White\nC. Denim blue\nD. Warm yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7953,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 127:   9%| | 128/1495 [00:45<06:
[Running Accuracy]: 0.7969,[Response]: D.<|endoftext|>, [Correct Ans]: Warm yellow, , [Prog]: 128:   9%| | 128/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?\nA. Black\nB. White\nC. Denim blue\nD. Warm yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Whether the giraffe is emphasized in the center of the composition
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Whether the giraffe is emphasized in the center of the composition
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Whether the giraffe is emphasized in the center of the composition\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7969,[Response]: D.<|endoftext|>, [Correct Ans]: Warm yellow, , [Prog]: 128:   9%| | 129/1495 [0
[Running Accuracy]: 0.7984,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 129:   9%| | 129/1495 [00:45<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Whether the giraffe is emphasized in the center of the composition\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the character face contain rich texture in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the character face contain rich texture in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the character face contain rich texture in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7984,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 129:   9%| | 130/1495 [00:46<06:
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 130:   9%| | 130/1495 [00:46<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the character face contain rich texture in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color vividity of the tree?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color vividity of the tree?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color vividity of the tree?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 130:   9%| | 131/1495 [00:46<06:
[Running Accuracy]: 0.8015,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 131:   9%| | 131/1495 [00:46<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color vividity of the tree?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the furry thing in this image the focal point?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the furry thing in this image the focal point?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the furry thing in this image the focal point?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8015,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 131:   9%| | 132/1495 [00:46<06
[Running Accuracy]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 132:   9%| | 132/1495 [00:46<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the furry thing in this image the focal point?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. White
B. Black
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. White
B. Black
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. White\nB. Black\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 132:   9%| | 133/1495 [00:46<06:
[Running Accuracy]: 0.7970,[Response]: A.<|endoftext|>, [Correct Ans]: White, , [Prog]: 133:   9%| | 133/1495 [00:46<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. White\nB. Black\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the characters in the image?
A. Green
B. Yellow
C. Purple
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color scheme of the characters in the image?
A. Green
B. Yellow
C. Purple
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color scheme of the characters in the image?\nA. Green\nB. Yellow\nC. Purple\nD. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7970,[Response]: A.<|endoftext|>, [Correct Ans]: White, , [Prog]: 133:   9%| | 134/1495 [00:47<0
[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 134:   9%| | 134/1495 [00:47<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the characters in the image?\nA. Green\nB. Yellow\nC. Purple\nD. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the leaves the brightest part of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the leaves the brightest part of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the leaves the brightest part of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 134:   9%| | 135/1495 [00:47<0
[Running Accuracy]: 0.7926,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 135:   9%| | 135/1495 [00:47<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the leaves the brightest part of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7926,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 135:   9%| | 136/1495 [00:48<10:
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 136:   9%| | 136/1495 [00:48<10:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 136:   9%| | 137/1495 [00:48<09:
[Running Accuracy]: 0.7883,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 137:   9%| | 137/1495 [00:48<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there motion blur in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there motion blur in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7883,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 137:   9%| | 138/1495 [00:49<
[Running Accuracy]: 0.7899,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 138:   9%| | 138/1495 [00:49<09:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there motion blur in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the clearest?
A. Ground
B. Building
C. Stool with chains
D. Car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the clearest?
A. Ground
B. Building
C. Stool with chains
D. Car
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the clearest?\nA. Ground\nB. Building\nC. Stool with chains\nD. Car\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7899,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 138:   9%| | 139/1495 [00:49<08:3
[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Stool with chains, , [Prog]: 139:   9%| | 139/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the clearest?\nA. Ground\nB. Building\nC. Stool with chains\nD. Car\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object appears the brightest in this image?
A. Left 2
B. Left 1
C. Right 2
D. Right 1
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object appears the brightest in this image?
A. Left 2
B. Left 1
C. Right 2
D. Right 1
Answer with the option's letter from the given choices directly.

prompts: [["Which object appears the brightest in this image?\nA. Left 2\nB. Left 1\nC. Right 2\nD. Right 1\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Stool with chains, , [Prog]: 139:   9%| | 140/1
[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Left 1, , [Prog]: 140:   9%| | 140/1495 [00:49<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object appears the brightest in this image?\nA. Left 2\nB. Left 1\nC. Right 2\nD. Right 1\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there recurring patterns in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there recurring patterns in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Left 1, , [Prog]: 140:   9%| | 141/1495 [00:50<
[Running Accuracy]: 0.7872,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 141:   9%| | 141/1495 [00:50<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7872,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 141:   9%| | 142/1495 [00:50<07:
[Running Accuracy]: 0.7887,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 142:   9%| | 142/1495 [00:50<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7887,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 142:  10%| | 143/1495 [00:50<
[Running Accuracy]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 143:  10%| | 143/1495 [00:50<07:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Wall
B. Cup
C. Spoon
D. Beverage
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Wall
B. Cup
C. Spoon
D. Beverage
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Wall\nB. Cup\nC. Spoon\nD. Beverage\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 143:  10%| | 144/1495 [00:50<07:0
[Running Accuracy]: 0.7847,[Response]: D.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 144:  10%| | 144/1495 [00:50<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Wall\nB. Cup\nC. Spoon\nD. Beverage\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues are present in the image?
A. Overexposure
B. Backlighting
C. Compression artifacts
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues are present in the image?
A. Overexposure
B. Backlighting
C. Compression artifacts
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What issues are present in the image?\nA. Overexposure\nB. Backlighting\nC. Compression artifacts\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7847,[Response]: D.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 144:  10%| | 145/1495 [00:51<07:
[Running Accuracy]: 0.7862,[Response]: B.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 145:  10%| | 145/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues are present in the image?\nA. Overexposure\nB. Backlighting\nC. Compression artifacts\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7862,[Response]: B.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 145:  10%| | 146/1495 [
[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 146:  10%| | 146/1495 [00:51<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 146:  10%| | 147/1495 [00:51<0
[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 147:  10%| | 147/1495 [00:51<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Doe the human in the image look realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Doe the human in the image look realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Doe the human in the image look realistic?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 147:  10%| | 148/1495 [00:52<07
[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 148:  10%| | 148/1495 [00:52<07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Doe the human in the image look realistic?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stone pile the main subject of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the stone pile the main subject of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the stone pile the main subject of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 148:  10%| | 149/1495 [00:52<07:0
[Running Accuracy]: 0.7852,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 149:  10%| | 149/1495 [00:52<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stone pile the main subject of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7852,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 149:  10%| | 150/1495 [00:52<06:
[Running Accuracy]: 0.7867,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 150:  10%| | 150/1495 [00:52<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the doll in the lower left corner of the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the doll in the lower left corner of the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the doll in the lower left corner of the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7867,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 150:  10%| | 151/1495 [00:53<06:
[Running Accuracy]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 151:  10%| | 151/1495 [00:53<06:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the doll in the lower left corner of the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 151:  10%| | 152/1495 [00:53<06:3
[Running Accuracy]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 152:  10%| | 152/1495 [00:53
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Blue
B. Black
C. Light gray
D. White
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Blue
B. Black
C. Light gray
D. White
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Blue\nB. Black\nC. Light gray\nD. White\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 152:  10%| | 153/1495 [00:53
[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Black, , [Prog]: 153:  10%| | 153/1495 [00:53<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Blue\nB. Black\nC. Light gray\nD. White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man on the left side of the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man on the left side of the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man on the left side of the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Black, , [Prog]: 153:  10%| | 154/1495 [00:53<0
[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 154:  10%| | 154/1495 [00:53<06:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man on the left side of the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?
A. Grass
B. Little girl
C. Road
D. Road bump
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of the image?
A. Grass
B. Little girl
C. Road
D. Road bump
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Grass\nB. Little girl\nC. Road\nD. Road bump\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B

[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 154:  10%| | 155/1495 [00:54<06:1
[Running Accuracy]: 0.7742,[Response]: B<|endoftext|>, [Correct Ans]: Little girl, , [Prog]: 155:  10%| | 155/1495 [00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?\nA. Grass\nB. Little girl\nC. Road\nD. Road bump\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is motion-blurred?
A. The motorcycle
B. The background
C. The man
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is motion-blurred?
A. The motorcycle
B. The background
C. The man
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is motion-blurred?\nA. The motorcycle\nB. The background\nC. The man\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7742,[Response]: B<|endoftext|>, [Correct Ans]: Little girl, , [Prog]: 155:  10%| | 156/1495 [00
[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: The background, , [Prog]: 156:  10%| | 156/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is motion-blurred?\nA. The motorcycle\nB. The background\nC. The man\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dark
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: The background, , [Prog]: 156:  11%| | 157/1495
[Running Accuracy]: 0.7707,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 157:  11%| | 157/1495 [00:54<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dark\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Acceptable\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7707,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 157:  11%| | 158/1495 [00:55<08
[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 158:  11%| | 158/1495 [00:55<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Acceptable\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers on the two trees bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers on the two trees bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers on the two trees bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 158:  11%| | 159/1495 [00:55<07
[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 159:  11%| | 159/1495 [00:55<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers on the two trees bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality problems exist in the image?
A. Overexposure
B. Noise
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality problems exist in the image?
A. Overexposure
B. Noise
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What quality problems exist in the image?\nA. Overexposure\nB. Noise\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 159:  11%| | 160/1495 [00:55<07:
[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 160:  11%| | 160/1495 [00:55<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality problems exist in the image?\nA. Overexposure\nB. Noise\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the shark in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the shark in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the shark in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 160:  11%| | 161/1495 [00:56<0
[Running Accuracy]: 0.7702,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 161:  11%| | 161/1495 [00:56<07:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the shark in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7702,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 161:  11%| | 162/1495 [00:56<07:1
[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 162:  11%| | 162/1495 [00:56<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 162:  11%| | 163/1495 [00:57<08:
[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 163:  11%| | 163/1495 [00:57<08:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color in this image?
A. Monotonous
B. Vivid
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color in this image?
A. Monotonous
B. Vivid
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color in this image?\nA. Monotonous\nB. Vivid\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 163:  11%| | 164/1495 [00:57<07:5
[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 164:  11%| | 164/1495 [00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color in this image?\nA. Monotonous\nB. Vivid\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 164:  11%| | 165/1495 [00
[Running Accuracy]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 165:  11%| | 165/1495 [00:57<08:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Slightly blurry
B. Not blurry at all
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Slightly blurry
B. Not blurry at all
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Slightly blurry\nB. Not blurry at all\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 165:  11%| | 166/1495 [00:58<08:1
[Running Accuracy]: 0.7771,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 166:  11%| | 166/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Slightly blurry\nB. Not blurry at all\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the goldfish in this image?
A. Monotonous
B. Vibrant
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the goldfish in this image?
A. Monotonous
B. Vibrant
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the goldfish in this image?\nA. Monotonous\nB. Vibrant\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7771,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 166:  11%| | 167/1495 [0
[Running Accuracy]: 0.7725,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 167:  11%| | 167/1495 [00:58
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the goldfish in this image?\nA. Monotonous\nB. Vibrant\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any color fringing in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any color fringing in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there any color fringing in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7725,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 167:  11%| | 168/1495 [00:58
[Running Accuracy]: 0.7738,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 168:  11%| | 168/1495 [00:58<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any color fringing in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image of the beast?
A. Average
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image of the beast?
A. Average
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image of the beast?\nA. Average\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7738,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 168:  11%| | 169/1495 [00:59<07:
[Running Accuracy]: 0.7751,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 169:  11%| | 169/1495 [00:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image of the beast?\nA. Average\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Noise
B. Blur
C. Low light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Noise
B. Blur
C. Low light
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Noise\nB. Blur\nC. Low light\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7751,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 169:  11%| | 170/1495 [00:59<0
[Running Accuracy]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 170:  11%| | 170/1495 [00:59<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Noise\nB. Blur\nC. Low light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image has the highest color saturation?
A. The red object on the right side of the image
B. The lower right corner of the image
C. The ground at the bottom of the image
D. The shoes on the right side of the image
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image has the highest color saturation?
A. The red object on the right side of the image
B. The lower right corner of the image
C. The ground at the bottom of the image
D. The shoes on the right side of the image
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image has the highest color saturation?\nA. The red object on the right side of the image\nB. The lower right corner of the image\nC. The ground at the bottom of the image\nD. The shoes on the right side of the image\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 170:  11%| | 171/1495 [00:59<07
[Running Accuracy]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: The red object on the right side of the image, 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image has the highest color saturation?\nA. The red object on the right side of the image\nB. The lower right corner of the image\nC. The ground at the bottom of the image\nD. The shoes on the right side of the image\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part in this image?
A. Two walking girls
B. Buildings
C. Streetlights
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part in this image?
A. Two walking girls
B. Buildings
C. Streetlights
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part in this image?\nA. Two walking girls\nB. Buildings\nC. Streetlights\nD. Trees\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: The red object on the right side of the image, 
[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Two walking girls, , [Prog]: 172:  12%| | 172/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part in this image?\nA. Two walking girls\nB. Buildings\nC. Streetlights\nD. Trees\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion doesn't appear in this picture?
A. Overexposure
B. Motion blur
C. Out of focus
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion doesn't appear in this picture?
A. Overexposure
B. Motion blur
C. Out of focus
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion doesn't appear in this picture?\nA. Overexposure\nB. Motion blur\nC. Out of focus\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Two walking girls, , [Prog]: 172:  12%| | 173/1
[Running Accuracy]: 0.7746,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 173:  12%| | 173/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion doesn't appear in this picture?\nA. Overexposure\nB. Motion blur\nC. Out of focus\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast level of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7746,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 173:  12%| | 174/1495 [
[Running Accuracy]: 0.7759,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 174:  12%| | 174/1495 [01:00<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Noise
B. Artifact
C. Overexposure
D. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Noise
B. Artifact
C. Overexposure
D. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Noise\nB. Artifact\nC. Overexposure\nD. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7759,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 174:  12%| | 175/1495 [01:01<09:
[Running Accuracy]: 0.7771,[Response]: D.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 175:  12%| | 175/1495 [01:01<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Noise\nB. Artifact\nC. Overexposure\nD. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition of this image?
A. Symmetrical
B. Pyramidal
C. Centric
D. Other
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the composition of this image?
A. Symmetrical
B. Pyramidal
C. Centric
D. Other
Answer with the option's letter from the given choices directly.

prompts: [["What is the composition of this image?\nA. Symmetrical\nB. Pyramidal\nC. Centric\nD. Other\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7771,[Response]: D.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 175:  12%| | 176/1495 [01:01<08
[Running Accuracy]: 0.7727,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 176:  12%| | 176/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition of this image?\nA. Symmetrical\nB. Pyramidal\nC. Centric\nD. Other\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is not affected by motion blur?
A. Building
B. Red car
C. Fountain
D. Blue car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is not affected by motion blur?
A. Building
B. Red car
C. Fountain
D. Blue car
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is not affected by motion blur?\nA. Building\nB. Red car\nC. Fountain\nD. Blue car\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7727,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 176:  12%| | 177/1495 [0
[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Red car, , [Prog]: 177:  12%| | 177/1495 [01:02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is not affected by motion blur?\nA. Building\nB. Red car\nC. Fountain\nD. Blue car\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Completely clear
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Completely clear
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Completely clear\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Red car, , [Prog]: 177:  12%| | 178/1495 [01:02
[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Completely clear, , [Prog]: 178:  12%| | 178/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Completely clear\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which kind of image quality problem does not exist in this image?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which kind of image quality problem does not exist in this image?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which kind of image quality problem does not exist in this image?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Completely clear, , [Prog]: 178:  12%| | 179/14
[Running Accuracy]: 0.7709,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 179:  12%| | 179/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which kind of image quality problem does not exist in this image?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is positioned in the center to be emphasized in this photo?
A. The bear
B. The woman
C. The boy
D. The girl
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is positioned in the center to be emphasized in this photo?
A. The bear
B. The woman
C. The boy
D. The girl
Answer with the option's letter from the given choices directly.

prompts: [["Which object is positioned in the center to be emphasized in this photo?\nA. The bear\nB. The woman\nC. The boy\nD. The girl\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 179:  12%| | 180/1495 
[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: The bear, , [Prog]: 180:  12%| | 180/1495 [01:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is positioned in the center to be emphasized in this photo?\nA. The bear\nB. The woman\nC. The boy\nD. The girl\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion occurs in this image?
A. Underexposure
B. Compression Artifacts
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion occurs in this image?
A. Underexposure
B. Compression Artifacts
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion occurs in this image?\nA. Underexposure\nB. Compression Artifacts\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: The bear, , [Prog]: 180:  12%| | 181/1495 [01:0
[Running Accuracy]: 0.7735,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 181:  12%| | 181/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion occurs in this image?\nA. Underexposure\nB. Compression Artifacts\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7735,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 181:  12%| | 182/1495 [0
[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 182:  12%| | 182/1495 [01:03<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 182:  12%| | 183/1495 [01:04<07
[Running Accuracy]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 183:  12%| | 183/1495 [01:04<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 183:  12%| | 184/1495 [01:04<07
[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 184:  12%| | 184/1495 [01:04<07:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is not present in this image?
A. White
B. Blue
C. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is not present in this image?
A. White
B. Blue
C. Red
Answer with the option's letter from the given choices directly.

prompts: [["Which color is not present in this image?\nA. White\nB. Blue\nC. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 184:  12%| | 185/1495 [01:04<07:1
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 185:  12%| | 185/1495 [01:04<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is not present in this image?\nA. White\nB. Blue\nC. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blur exists in the hand-holding couple in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blur exists in the hand-holding couple in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of blur exists in the hand-holding couple in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 185:  12%| | 186/1495 [01:05<07
[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 186:  12%| | 186/1495 [01:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blur exists in the hand-holding couple in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Bright
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Dark\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 186:  13%|▏| 187/1495 [01:05<
[Running Accuracy]: 0.7807,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 187:  13%|▏| 187/1495 [01:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Bright\nB. Dark\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Overexposure
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Overexposure
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7807,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 187:  13%|▏| 188/1495 [01:05<
[Running Accuracy]: 0.7819,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 188:  13%|▏| 188/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Low light
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Low light
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Low light\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C. Blur

[Running Accuracy]: 0.7819,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 188:  13%|▏| 189/1495 
[Running Accuracy]: 0.7831,[Response]: C. Blur<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 189:  13%|▏| 189/1495 [01:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Low light\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C. Blur<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of the image good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clarity of the image good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the clarity of the image good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7831,[Response]: C. Blur<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 189:  13%|▏| 190/1495 [01:
[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 190:  13%|▏| 190/1495 [01:07<10:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of the image good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Null
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Null
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Null\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 190:  13%|▏| 191/1495 [01:07<09:
[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 191:  13%|▏| 191/1495 [01:07<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Null\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 191:  13%|▏| 192/1495 [01:07<08
[Running Accuracy]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 192:  13%|▏| 192/1495 [01:07<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall and ceiling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise on the wall and ceiling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise on the wall and ceiling?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 192:  13%|▏| 193/1495 [01:08<09
[Running Accuracy]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 193:  13%|▏| 193/1495 [01:08<09:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall and ceiling?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is this image?
A. Slightly
B. Severely
C. Moderately
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is this image?
A. Slightly
B. Severely
C. Moderately
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is this image?\nA. Slightly\nB. Severely\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 193:  13%|▏| 194/1495 [01:08<08:
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 194:  13%|▏| 194/1495 [01:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is this image?\nA. Slightly\nB. Severely\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 194:  13%|▏| 195/1495 [01:0
[Running Accuracy]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 195:  13%|▏| 195/1495 [01:08<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the dragon fly in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the dragon fly in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the dragon fly in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 195:  13%|▏| 196/1495 [01:08<0
[Running Accuracy]: 0.7857,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 196:  13%|▏| 196/1495 [01:08<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the dragon fly in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is in this image?
A. Faded color
B. Overexposure
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion is in this image?
A. Faded color
B. Overexposure
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion is in this image?\nA. Faded color\nB. Overexposure\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7857,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 196:  13%|▏| 197/1495 [01:09<07
[Running Accuracy]: 0.7868,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 197:  13%|▏| 197/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is in this image?\nA. Faded color\nB. Overexposure\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?
A. Relatively dark
B. Extremely dark
C. Bright
D. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Relatively dark
B. Extremely dark
C. Bright
D. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Relatively dark\nB. Extremely dark\nC. Bright\nD. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7868,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 197:  13%|▏| 198/1495 [
[Running Accuracy]: 0.7879,[Response]: B.<|endoftext|>, [Correct Ans]: Extremely dark, , [Prog]: 198:  13%|▏| 198/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?\nA. Relatively dark\nB. Extremely dark\nC. Bright\nD. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7879,[Response]: B.<|endoftext|>, [Correct Ans]: Extremely dark, , [Prog]: 198:  13%|▏| 199/1495
[Running Accuracy]: 0.7889,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 199:  13%|▏| 199/1495 [01:09<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any noise spots in the location of the man in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any noise spots in the location of the man in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there any noise spots in the location of the man in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7889,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 199:  13%|▏| 200/1495 [01:10<06:
[Running Accuracy]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 200:  13%|▏| 200/1495 [01:10<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any noise spots in the location of the man in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture brighter in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture brighter in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture brighter in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 200:  13%|▏| 201/1495 [01:10<06:
[Running Accuracy]: 0.7861,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 201:  13%|▏| 201/1495 [01:10<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture brighter in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7861,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 201:  14%|▏| 202/1495 [01:10<06:
[Running Accuracy]: 0.7871,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 202:  14%|▏| 202/1495 [01:10<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7871,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 202:  14%|▏| 203/1495 [01:11<06:
[Running Accuracy]: 0.7882,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 203:  14%|▏| 203/1495 [01:11<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the subject emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the subject emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7882,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 203:  14%|▏| 204/1495 [01:11<06:
[Running Accuracy]: 0.7892,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 204:  14%|▏| 204/1495 [01:11<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Blur
B. Noise
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Blur
B. Noise
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Blur\nB. Noise\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7892,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 204:  14%|▏| 205/1495 [01:11<06:
[Running Accuracy]: 0.7902,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 205:  14%|▏| 205/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Blur\nB. Noise\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main focus of this image?
A. The cactus
B. The building
C. The sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main focus of this image?
A. The cactus
B. The building
C. The sky
Answer with the option's letter from the given choices directly.

prompts: [["What is the main focus of this image?\nA. The cactus\nB. The building\nC. The sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7902,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 205:  14%|▏| 206/1495
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: The cactus, , [Prog]: 206:  14%|▏| 206/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main focus of this image?\nA. The cactus\nB. The building\nC. The sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: The cactus, , [Prog]: 206:  14%|▏| 207/1495 [01
[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 207:  14%|▏| 207/1495 [01:12<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 207:  14%|▏| 208/1495 [01:12<06:
[Running Accuracy]: 0.7933,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 208:  14%|▏| 208/1495 [01:12<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7933,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 208:  14%|▏| 209/1495 [01:12<06:
[Running Accuracy]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 209:  14%|▏| 209/1495 [01:12<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What caused the digits on the clock to be hardly unrecognizable?
A. Underexposure
B. Motion Blur
C. Severe Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What caused the digits on the clock to be hardly unrecognizable?
A. Underexposure
B. Motion Blur
C. Severe Noise
Answer with the option's letter from the given choices directly.

prompts: [["What caused the digits on the clock to be hardly unrecognizable?\nA. Underexposure\nB. Motion Blur\nC. Severe Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 209:  14%|▏| 210/1495 [01:13<06
[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 210:  14%|▏| 210/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What caused the digits on the clock to be hardly unrecognizable?\nA. Underexposure\nB. Motion Blur\nC. Severe Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 210:  14%|▏| 211/1495 [0
[Running Accuracy]: 0.7962,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 211:  14%|▏| 211/1495 [01:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the flowers in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the flowers in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7962,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 211:  14%|▏| 212/1495 [01:1
[Running Accuracy]: 0.7972,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 212:  14%|▏| 212/1495 [01:13<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image rich in color?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7972,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 212:  14%|▏| 213/1495 [01:13<06:
[Running Accuracy]: 0.7981,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 213:  14%|▏| 213/1495 [01:13<06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image rich in color?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the main focus in the image?
A. Blanket
B. Teddy bear
C. Carpet
D. Cabinet
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the main focus in the image?
A. Blanket
B. Teddy bear
C. Carpet
D. Cabinet
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the main focus in the image?\nA. Blanket\nB. Teddy bear\nC. Carpet\nD. Cabinet\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7981,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 213:  14%|▏| 214/1495 [01:14<06:0
[Running Accuracy]: 0.7991,[Response]: B.<|endoftext|>, [Correct Ans]: Teddy bear, , [Prog]: 214:  14%|▏| 214/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the main focus in the image?\nA. Blanket\nB. Teddy bear\nC. Carpet\nD. Cabinet\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7991,[Response]: B.<|endoftext|>, [Correct Ans]: Teddy bear, , [Prog]: 214:  14%|▏| 215/1495 [01
[Running Accuracy]: 0.7953,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 215:  14%|▏| 215/1495 [01:14<06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?
A. Grass
B. Wildflower
C. Gorilla
D. Rock
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest object in the image?
A. Grass
B. Wildflower
C. Gorilla
D. Rock
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest object in the image?\nA. Grass\nB. Wildflower\nC. Gorilla\nD. Rock\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7953,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 215:  14%|▏| 216/1495 [01:14<06:0
[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Gorilla, , [Prog]: 216:  14%|▏| 216/1495 [01:14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?\nA. Grass\nB. Wildflower\nC. Gorilla\nD. Rock\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?
A. Grass
B. Crocodile
C. Flower
D. Rock
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, which object is emphasized in the center?
A. Grass
B. Crocodile
C. Flower
D. Rock
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, which object is emphasized in the center?\nA. Grass\nB. Crocodile\nC. Flower\nD. Rock\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Gorilla, , [Prog]: 216:  15%|▏| 217/1495 [01:15
[Running Accuracy]: 0.7972,[Response]: B.<|endoftext|>, [Correct Ans]: Crocodile, , [Prog]: 217:  15%|▏| 217/1495 [01:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?\nA. Grass\nB. Crocodile\nC. Flower\nD. Rock\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees blurry in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the trees blurry in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the trees blurry in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7972,[Response]: B.<|endoftext|>, [Correct Ans]: Crocodile, , [Prog]: 217:  15%|▏| 218/1495 [01:
[Running Accuracy]: 0.7936,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 218:  15%|▏| 218/1495 [01:15<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees blurry in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?
A. Pot
B. Oil
C. Green onion
D. Cake
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focal point in this image?
A. Pot
B. Oil
C. Green onion
D. Cake
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focal point in this image?\nA. Pot\nB. Oil\nC. Green onion\nD. Cake\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7936,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 218:  15%|▏| 219/1495 [01:15<06:
[Running Accuracy]: 0.7945,[Response]: D.<|endoftext|>, [Correct Ans]: Cake, , [Prog]: 219:  15%|▏| 219/1495 [01:15<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?\nA. Pot\nB. Oil\nC. Green onion\nD. Cake\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of the image?
A. Calmful
B. Terrifying
C. Pleasant
D. Cheerful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the feeling of the image?
A. Calmful
B. Terrifying
C. Pleasant
D. Cheerful
Answer with the option's letter from the given choices directly.

prompts: [["How is the feeling of the image?\nA. Calmful\nB. Terrifying\nC. Pleasant\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7945,[Response]: D.<|endoftext|>, [Correct Ans]: Cake, , [Prog]: 219:  15%|▏| 220/1495 [01:15<06
[Running Accuracy]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Terrifying, , [Prog]: 220:  15%|▏| 220/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of the image?\nA. Calmful\nB. Terrifying\nC. Pleasant\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the bird in the image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the bird in the image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the bird in the image?\nA. Clear\nB. Blurry\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Terrifying, , [Prog]: 220:  15%|▏| 221/1495 [01
[Running Accuracy]: 0.7919,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 221:  15%|▏| 221/1495 [01:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the bird in the image?\nA. Clear\nB. Blurry\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the visibilty of this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the visibilty of this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the visibilty of this image?\nA. Good\nB. Acceptable\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7919,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 221:  15%|▏| 222/1495 [01:16<0
[Running Accuracy]: 0.7928,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 222:  15%|▏| 222/1495 [01:16<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the visibilty of this image?\nA. Good\nB. Acceptable\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman's head or body clearer?
A. Her head
B. Her body
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman's head or body clearer?
A. Her head
B. Her body
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman's head or body clearer?\nA. Her head\nB. Her body\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7928,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 222:  15%|▏| 223/1495 [01:16<06
[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Her head, , [Prog]: 223:  15%|▏| 223/1495 [01:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman's head or body clearer?\nA. Her head\nB. Her body\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What pattern does not exist in this image?
A. Underexposure
B. Blur
C. Compression Artifact
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What pattern does not exist in this image?
A. Underexposure
B. Blur
C. Compression Artifact
Answer with the option's letter from the given choices directly.

prompts: [["What pattern does not exist in this image?\nA. Underexposure\nB. Blur\nC. Compression Artifact\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Her head, , [Prog]: 223:  15%|▏| 224/1495 [01:1
[Running Accuracy]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: Compression Artifact, , [Prog]: 224:  15%|▏| 22
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What pattern does not exist in this image?\nA. Underexposure\nB. Blur\nC. Compression Artifact\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: Compression Artifact, , [Prog]: 224:  15%|▏| 22
[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 225:  15%|▏| 225/1495 [01:17<06:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is affected by severe motion blur?
A. Tracks
B. Trees
C. People and roller coaster
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is affected by severe motion blur?
A. Tracks
B. Trees
C. People and roller coaster
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is affected by severe motion blur?\nA. Tracks\nB. Trees\nC. People and roller coaster\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 225:  15%|▏| 226/1495 [01:17<06:2
[Running Accuracy]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: People and roller coaster, , [Prog]: 226:  15%|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is affected by severe motion blur?\nA. Tracks\nB. Trees\nC. People and roller coaster\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the lizard contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the lizard contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the lizard contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: People and roller coaster, , [Prog]: 226:  15%|
[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 227:  15%|▏| 227/1495 [01:18<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the lizard contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the style of this image?
A. Photography
B. Impressionism
C. Animation
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the style of this image?
A. Photography
B. Impressionism
C. Animation
Answer with the option's letter from the given choices directly.

prompts: [["What is the style of this image?\nA. Photography\nB. Impressionism\nC. Animation\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 227:  15%|▏| 228/1495 [01:18<06:
[Running Accuracy]: 0.7939,[Response]: C.<|endoftext|>, [Correct Ans]: Animation, , [Prog]: 228:  15%|▏| 228/1495 [01:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the style of this image?\nA. Photography\nB. Impressionism\nC. Animation\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7939,[Response]: C.<|endoftext|>, [Correct Ans]: Animation, , [Prog]: 228:  15%|▏| 229/1495 [01:
[Running Accuracy]: 0.7948,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 229:  15%|▏| 229/1495 [01:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the sharpness of this image?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the sharpness of this image?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How good is the sharpness of this image?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7948,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 229:  15%|▏| 230/1495 [01:1
[Running Accuracy]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 230:  15%|▏| 230/1495 [01:19<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the sharpness of this image?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the photo has the highest color saturation?
A. Rock
B. Pine tree
C. Person
D. House
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the photo has the highest color saturation?
A. Rock
B. Pine tree
C. Person
D. House
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the photo has the highest color saturation?\nA. Rock\nB. Pine tree\nC. Person\nD. House\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 230:  15%|▏| 231/1495 [01:19<08
[Running Accuracy]: 0.7922,[Response]: C.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 231:  15%|▏| 231/1495 [01:19<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the photo has the highest color saturation?\nA. Rock\nB. Pine tree\nC. Person\nD. House\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is most severe in this image?
A. Noise
B. Overexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is most severe in this image?
A. Noise
B. Overexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is most severe in this image?\nA. Noise\nB. Overexposure\nC. Motion Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7922,[Response]: C.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 231:  16%|▏| 232/1495 [01:20<
[Running Accuracy]: 0.7931,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 232:  16%|▏| 232/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is most severe in this image?\nA. Noise\nB. Overexposure\nC. Motion Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image noisy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image noisy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image noisy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7931,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 232:  16%|▏| 233/1495 [0
[Running Accuracy]: 0.7940,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 233:  16%|▏| 233/1495 [01:20<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image noisy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7940,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 233:  16%|▏| 234/1495 [01:20<07:
[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 234:  16%|▏| 234/1495 [01:20<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the leaves in this image?
A. Vibrant
B. Monotonous
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the leaves in this image?
A. Vibrant
B. Monotonous
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the leaves in this image?\nA. Vibrant\nB. Monotonous\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 234:  16%|▏| 235/1495 [01:21<07
[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 235:  16%|▏| 235/1495 [01:21
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the leaves in this image?\nA. Vibrant\nB. Monotonous\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the robot in the image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the robot in the image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the robot in the image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 235:  16%|▏| 236/1495 [01:21
[Running Accuracy]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 236:  16%|▏| 236/1495 [01:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the robot in the image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 236:  16%|▏| 237/1495 [01:2
[Running Accuracy]: 0.7848,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 237:  16%|▏| 237/1495 [01:21<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat emphasized in the center of the composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat emphasized in the center of the composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat emphasized in the center of the composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7848,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 237:  16%|▏| 238/1495 [01:22<06:
[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 238:  16%|▏| 238/1495 [01:22<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat emphasized in the center of the composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the blurriness of the image?
A. Very blurry
B. Slightly blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the blurriness of the image?
A. Very blurry
B. Slightly blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How is the blurriness of the image?\nA. Very blurry\nB. Slightly blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 238:  16%|▏| 239/1495 [01:22<06:
[Running Accuracy]: 0.7866,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 239:  16%|▏| 239/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the blurriness of the image?\nA. Very blurry\nB. Slightly blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is overexposed?
A. The fish
B. The water
C. The coral
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is overexposed?
A. The fish
B. The water
C. The coral
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is overexposed?\nA. The fish\nB. The water\nC. The coral\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7866,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 239:  16%|▏| 240/149
[Running Accuracy]: 0.7875,[Response]: A.<|endoftext|>, [Correct Ans]: The fish, , [Prog]: 240:  16%|▏| 240/1495 [01:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is overexposed?\nA. The fish\nB. The water\nC. The coral\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an underexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7875,[Response]: A.<|endoftext|>, [Correct Ans]: The fish, , [Prog]: 240:  16%|▏| 241/1495 [01:2
[Running Accuracy]: 0.7884,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 241:  16%|▏| 241/1495 [01:22<06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7884,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 241:  16%|▏| 242/1495 [01:23<06:1
[Running Accuracy]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 242:  16%|▏| 242/1495 [01:23<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the rabbit emphasized in the center of this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the rabbit emphasized in the center of this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the rabbit emphasized in the center of this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 242:  16%|▏| 243/1495 [01:23<
[Running Accuracy]: 0.7901,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 243:  16%|▏| 243/1495 [01:23<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the rabbit emphasized in the center of this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7901,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 243:  16%|▏| 244/1495 [01:23<06:
[Running Accuracy]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 244:  16%|▏| 244/1495 [01:23<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the turtle toy in this image bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the turtle toy in this image bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the turtle toy in this image bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 244:  16%|▏| 245/1495 [01:24<06:
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 245:  16%|▏| 245/1495 [01:24<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the turtle toy in this image bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 245:  16%|▏| 246/1495 [01:24<06:
[Running Accuracy]: 0.7886,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 246:  16%|▏| 246/1495 [01:24<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?
A. Underexposure
B. Noise
C. Blurry
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does this image not have?
A. Underexposure
B. Noise
C. Blurry
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does this image not have?\nA. Underexposure\nB. Noise\nC. Blurry\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7886,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 246:  17%|▏| 247/1495 [01:24<06:
[Running Accuracy]: 0.7895,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 247:  17%|▏| 247/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?\nA. Underexposure\nB. Noise\nC. Blurry\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?
A. Motion blur
B. Overexposure
C. Out of focus
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Motion blur
B. Overexposure
C. Out of focus
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Motion blur\nB. Overexposure\nC. Out of focus\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7895,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 247:  17%|▏| 248/1495 [
[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 248:  17%|▏| 248/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?\nA. Motion blur\nB. Overexposure\nC. Out of focus\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What object is emphasized in the composition of the image?
A. Trees
B. Spider web
C. Deer
D. Grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What object is emphasized in the composition of the image?
A. Trees
B. Spider web
C. Deer
D. Grass
Answer with the option's letter from the given choices directly.

prompts: [["What object is emphasized in the composition of the image?\nA. Trees\nB. Spider web\nC. Deer\nD. Grass\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 248:  17%|▏| 249/1495 [
[Running Accuracy]: 0.7912,[Response]: C.<|endoftext|>, [Correct Ans]: Deer, , [Prog]: 249:  17%|▏| 249/1495 [01:25<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What object is emphasized in the composition of the image?\nA. Trees\nB. Spider web\nC. Deer\nD. Grass\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the people very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7912,[Response]: C.<|endoftext|>, [Correct Ans]: Deer, , [Prog]: 249:  17%|▏| 250/1495 [01:25<05
[Running Accuracy]: 0.7920,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 250:  17%|▏| 250/1495 [01:25<05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7920,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 250:  17%|▏| 251/1495 [01:25<05:5
[Running Accuracy]: 0.7928,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 251:  17%|▏| 251/1495 [01:25<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7928,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 251:  17%|▏| 252/1495 [01:26<05:
[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 252:  17%|▏| 252/1495 [01:26<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of the image?
A. Good
B. Poor
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of the image?
A. Good
B. Poor
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of the image?\nA. Good\nB. Poor\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 252:  17%|▏| 253/1495 [01:26<05
[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 253:  17%|▏| 253/1495 [01:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of the image?\nA. Good\nB. Poor\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 253:  17%|▏| 254/1495 [01:2
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 254:  17%|▏| 254/1495 [01:26<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 254:  17%|▏| 255/1495 [01:27<05
[Running Accuracy]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 255:  17%|▏| 255/1495 [01:27<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the object most severely affected by overexposure in the image?
A. Road sign
B. Bed
C. Telephone booth
D. Shop
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the object most severely affected by overexposure in the image?
A. Road sign
B. Bed
C. Telephone booth
D. Shop
Answer with the option's letter from the given choices directly.

prompts: [["What is the object most severely affected by overexposure in the image?\nA. Road sign\nB. Bed\nC. Telephone booth\nD. Shop\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 255:  17%|▏| 256/1495 [01:27<05:
[Running Accuracy]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: Bed, , [Prog]: 256:  17%|▏| 256/1495 [01:27<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the object most severely affected by overexposure in the image?\nA. Road sign\nB. Bed\nC. Telephone booth\nD. Shop\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting of the castle in this image?
A. Bright
B. Meidum
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting of the castle in this image?
A. Bright
B. Meidum
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting of the castle in this image?\nA. Bright\nB. Meidum\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: Bed, , [Prog]: 256:  17%|▏| 257/1495 [01:27<05:
[Running Accuracy]: 0.7860,[Response]: C.<|endoftext|>, [Correct Ans]: Meidum, , [Prog]: 257:  17%|▏| 257/1495 [01:27<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting of the castle in this image?\nA. Bright\nB. Meidum\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Blue
B. Green
C. Orange
D. Gray
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Blue
B. Green
C. Orange
D. Gray
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Blue\nB. Green\nC. Orange\nD. Gray\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7860,[Response]: C.<|endoftext|>, [Correct Ans]: Meidum, , [Prog]: 257:  17%|▏| 258/1495 [01:27<
[Running Accuracy]: 0.7868,[Response]: C.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 258:  17%|▏| 258/1495 [01:27<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Blue\nB. Green\nC. Orange\nD. Gray\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7868,[Response]: C.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 258:  17%|▏| 259/1495 [01:28<
[Running Accuracy]: 0.7876,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 259:  17%|▏| 259/1495 [01:28<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image appears the brightest?
A. Bicycle tires
B. House
C. Tree
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image appears the brightest?
A. Bicycle tires
B. House
C. Tree
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image appears the brightest?\nA. Bicycle tires\nB. House\nC. Tree\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7876,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 259:  17%|▏| 260/1495 [01:28<05
[Running Accuracy]: 0.7885,[Response]: A.<|endoftext|>, [Correct Ans]: Bicycle tires, , [Prog]: 260:  17%|▏| 260/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image appears the brightest?\nA. Bicycle tires\nB. House\nC. Tree\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any motion blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any motion blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any motion blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7885,[Response]: A.<|endoftext|>, [Correct Ans]: Bicycle tires, , [Prog]: 260:  17%|▏| 261/1495 
[Running Accuracy]: 0.7893,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 261:  17%|▏| 261/1495 [01:28<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any motion blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Noise
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Noise
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Noise\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7893,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 261:  18%|▏| 262/1495 [01:29<07:
[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 262:  18%|▏| 262/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Noise\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dog in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dog in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog in focus in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 262:  18%|▏| 263/1495 
[Running Accuracy]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 263:  18%|▏| 263/1495 [01:29<07:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dog in focus in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?
A. Over-exposure
B. Noise
C. Low light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of this image?
A. Over-exposure
B. Noise
C. Low light
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of this image?\nA. Over-exposure\nB. Noise\nC. Low light\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 263:  18%|▏| 264/1495 [01:29<06:4
[Running Accuracy]: 0.7917,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 264:  18%|▏| 264/1495 [01:29<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?\nA. Over-exposure\nB. Noise\nC. Low light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Blue
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Blue
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Blue\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7917,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 264:  18%|▏| 265/1495 [01:30<0
[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 265:  18%|▏| 265/1495 [01:30<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Blue\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. Wall
B. Printing machine
C. Ground
D. Keyboard
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. Wall
B. Printing machine
C. Ground
D. Keyboard
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. Wall\nB. Printing machine\nC. Ground\nD. Keyboard\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 265:  18%|▏| 266/1495 [01:30<0
[Running Accuracy]: 0.7895,[Response]: D.<|endoftext|>, [Correct Ans]: Printing machine, , [Prog]: 266:  18%|▏| 266/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. Wall\nB. Printing machine\nC. Ground\nD. Keyboard\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7895,[Response]: D.<|endoftext|>, [Correct Ans]: Printing machine, , [Prog]: 266:  18%|▏| 267/14
[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 267:  18%|▏| 267/1495 [01:30<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Would you say the composition in this image is good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Would you say the composition in this image is good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 267:  18%|▏| 268/1495 [01:31<06:
[Running Accuracy]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 268:  18%|▏| 268/1495 [01:31<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the building in this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the building in this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the building in this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 268:  18%|▏| 269/1495 [01:31<06:
[Running Accuracy]: 0.7918,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 269:  18%|▏| 269/1495 [01:31<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the building in this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from the top?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the light in this image come from the top?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the light in this image come from the top?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7918,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 269:  18%|▏| 270/1495 [01:31<
[Running Accuracy]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 270:  18%|▏| 270/1495 [01:31<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from the top?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Good\nB. Bad\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 270:  18%|▏| 271/1495 [01:31<06:
[Running Accuracy]: 0.7860,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 271:  18%|▏| 271/1495 [01:31<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Good\nB. Bad\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?
A. Intermediate
B. Monotonous
C. Vivid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the image?
A. Intermediate
B. Monotonous
C. Vivid
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the image?\nA. Intermediate\nB. Monotonous\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7860,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 271:  18%|▏| 272/1495 [01:32<05
[Running Accuracy]: 0.7868,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 272:  18%|▏| 272/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?\nA. Intermediate\nB. Monotonous\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness exists in the pedestrians on the street in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blurriness exists in the pedestrians on the street in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness exists in the pedestrians on the street in this image?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7868,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 272:  18%|▏| 273/1495 [01
[Running Accuracy]: 0.7839,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 273:  18%|▏| 273/1495 [01:32<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness exists in the pedestrians on the street in this image?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent are the two people in front of the building with umbrellas blurred in this image?
A. Severely
B. Slightly
C. Moderately
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent are the two people in front of the building with umbrellas blurred in this image?
A. Severely
B. Slightly
C. Moderately
Answer with the option's letter from the given choices directly.

prompts: [["To what extent are the two people in front of the building with umbrellas blurred in this image?\nA. Severely\nB. Slightly\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7839,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 273:  18%|▏| 274/1495 [01:32<
[Running Accuracy]: 0.7810,[Response]: C.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 274:  18%|▏| 274/1495 [01:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent are the two people in front of the building with umbrellas blurred in this image?\nA. Severely\nB. Slightly\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Normal
C. Colorful
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7810,[Response]: C.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 274:  18%|▏| 275/1495 [01:3
[Running Accuracy]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 275:  18%|▏| 275/1495 [01:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?
A. Poor
B. Meidum
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus in this image?
A. Poor
B. Meidum
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus in this image?\nA. Poor\nB. Meidum\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 275:  18%|▏| 276/1495 [01:3
[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 276:  18%|▏| 276/1495 [01:33<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?\nA. Poor\nB. Meidum\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion occurs in the image?
A. Out of focus
B. Noise
C. Motion blur
D. Compresssion Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion occurs in the image?
A. Out of focus
B. Noise
C. Motion blur
D. Compresssion Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What distortion occurs in the image?\nA. Out of focus\nB. Noise\nC. Motion blur\nD. Compresssion Artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 276:  19%|▏| 277/1495 [01:34<08
[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 277:  19%|▏| 277/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion occurs in the image?\nA. Out of focus\nB. Noise\nC. Motion blur\nD. Compresssion Artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the arrangement of elements in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the arrangement of elements in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the arrangement of elements in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 277:  19%|▏| 278/1495 [
[Running Accuracy]: 0.7842,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 278:  19%|▏| 278/1495 [01:34<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the arrangement of elements in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Wall
B. Little dog
C. Monitor
D. Keyboard
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Wall
B. Little dog
C. Monitor
D. Keyboard
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Wall\nB. Little dog\nC. Monitor\nD. Keyboard\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7842,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 278:  19%|▏| 279/1495 [01:34<07
[Running Accuracy]: 0.7849,[Response]: B.<|endoftext|>, [Correct Ans]: Little dog, , [Prog]: 279:  19%|▏| 279/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Wall\nB. Little dog\nC. Monitor\nD. Keyboard\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7849,[Response]: B.<|endoftext|>, [Correct Ans]: Little dog, , [Prog]: 279:  19%|▏| 280/1495 [01
[Running Accuracy]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 280:  19%|▏| 280/1495 [01:35<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?
A. Dim
B. Average
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Dim
B. Average
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Dim\nB. Average\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 280:  19%|▏| 281/1495 [01:35<06:
[Running Accuracy]: 0.7829,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 281:  19%|▏| 281/1495 [01:35<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?\nA. Dim\nB. Average\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there excessive noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there excessive noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there excessive noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7829,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 281:  19%|▏| 282/1495 [01:35<06:
[Running Accuracy]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 282:  19%|▏| 282/1495 [01:35<06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there excessive noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?
A. noise
B. underexposure
C. overexposure
D. out-of-focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does this image not have?
A. noise
B. underexposure
C. overexposure
D. out-of-focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does this image not have?\nA. noise\nB. underexposure\nC. overexposure\nD. out-of-focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 282:  19%|▏| 283/1495 [01:35<06:0
[Running Accuracy]: 0.7845,[Response]: C.<|endoftext|>, [Correct Ans]: overexposure, , [Prog]: 283:  19%|▏| 283/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?\nA. noise\nB. underexposure\nC. overexposure\nD. out-of-focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the image like?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the image like?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the image like?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7845,[Response]: C.<|endoftext|>, [Correct Ans]: overexposure, , [Prog]: 283:  19%|▏| 284/1495 [
[Running Accuracy]: 0.7852,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 284:  19%|▏| 284/1495 [01:36<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the image like?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in the image?
A. Underexposure
B. Distortion
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does not exist in the image?
A. Underexposure
B. Distortion
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does not exist in the image?\nA. Underexposure\nB. Distortion\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7852,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 284:  19%|▏| 285/1495 [01:36<05
[Running Accuracy]: 0.7860,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 285:  19%|▏| 285/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in the image?\nA. Underexposure\nB. Distortion\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Bright
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Bright
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Bright\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7860,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 285:  19%|▏| 286/1495 
[Running Accuracy]: 0.7867,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 286:  19%|▏| 286/1495 [01:36<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Bright\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7867,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 286:  19%|▏| 287/1495 [01:37<05
[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 287:  19%|▏| 287/1495 [01:37<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the parrot in the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the parrot in the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the parrot in the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 287:  19%|▏| 288/1495 [01:37<05:
[Running Accuracy]: 0.7882,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 288:  19%|▏| 288/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the parrot in the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image quality issue does this image have?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image quality issue does this image have?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which image quality issue does this image have?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7882,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 288:  19%|▏| 289/149
[Running Accuracy]: 0.7889,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 289:  19%|▏| 289/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image quality issue does this image have?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7889,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 289:  19%|▏| 290/1495 
[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 290:  19%|▏| 290/1495 [01:37<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Very blurry
C. A little blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Very blurry
C. A little blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. A little blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 290:  19%|▏| 291/1495 [01:38<06:
[Running Accuracy]: 0.7869,[Response]: B.<|endoftext|>, [Correct Ans]: A little blurry, , [Prog]: 291:  19%|▏| 291/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. A little blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7869,[Response]: B.<|endoftext|>, [Correct Ans]: A little blurry, , [Prog]: 291:  20%|▏| 292/149
[Running Accuracy]: 0.7877,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 292:  20%|▏| 292/1495 [01:38<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main object in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main object in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7877,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 292:  20%|▏| 293/1495 [01:38<06
[Running Accuracy]: 0.7884,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 293:  20%|▏| 293/1495 [01:38<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the monster emphasized in the center of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the monster emphasized in the center of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the monster emphasized in the center of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7884,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 293:  20%|▏| 294/1495 [01:39<05:
[Running Accuracy]: 0.7891,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 294:  20%|▏| 294/1495 [01:39<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the monster emphasized in the center of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show shallow depth-of-field?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image show shallow depth-of-field?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image show shallow depth-of-field?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7891,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 294:  20%|▏| 295/1495 [01:39<05:
[Running Accuracy]: 0.7898,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 295:  20%|▏| 295/1495 [01:39<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show shallow depth-of-field?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degrades the quality of the image?
A. Blur
B. Fade
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degrades the quality of the image?
A. Blur
B. Fade
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What degrades the quality of the image?\nA. Blur\nB. Fade\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7898,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 295:  20%|▏| 296/1495 [01:39<05:
[Running Accuracy]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 296:  20%|▏| 296/1495 [01:39<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degrades the quality of the image?\nA. Blur\nB. Fade\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the athlete wearing a blue outfit clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the athlete wearing a blue outfit clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the athlete wearing a blue outfit clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 296:  20%|▏| 297/1495 [01:40<05
[Running Accuracy]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 297:  20%|▏| 297/1495 [01:40<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the athlete wearing a blue outfit clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of colors in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of colors in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of colors in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 297:  20%|▏| 298/1495 [01:40<05:
[Running Accuracy]: 0.7886,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 298:  20%|▏| 298/1495 [01:40<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of colors in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the person in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7886,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 298:  20%|▏| 299/1495 [01:40<05:
[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 299:  20%|▏| 299/1495 [01:40<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the stool in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the stool in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the stool in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 299:  20%|▏| 300/1495 [01:40<05:5
[Running Accuracy]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 300:  20%|▏| 300/1495 [01:40<05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the stool in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the wood contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the wood contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the wood contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 300:  20%|▏| 301/1495 [01:41<05:5
[Running Accuracy]: 0.7907,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 301:  20%|▏| 301/1495 [01:41<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the wood contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the colors of the main objects in the image vivid?
A. Monotonous
B. Moderate
C. Vivid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the colors of the main objects in the image vivid?
A. Monotonous
B. Moderate
C. Vivid
Answer with the option's letter from the given choices directly.

prompts: [["Are the colors of the main objects in the image vivid?\nA. Monotonous\nB. Moderate\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7907,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 301:  20%|▏| 302/1495 [01:41<05:
[Running Accuracy]: 0.7881,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 302:  20%|▏| 302/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the colors of the main objects in the image vivid?\nA. Monotonous\nB. Moderate\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7881,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 302:  20%|▏| 303/1495 [01
[Running Accuracy]: 0.7888,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 303:  20%|▏| 303/1495 [01:41<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the boat emphasized as the center in the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the boat emphasized as the center in the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the boat emphasized as the center in the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7888,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 303:  20%|▏| 304/1495 [01:42<05:
[Running Accuracy]: 0.7895,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 304:  20%|▏| 304/1495 [01:42<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the boat emphasized as the center in the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7895,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 304:  20%|▏| 305/1495 [01:42<05:
[Running Accuracy]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 305:  20%|▏| 305/1495 [01:42<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from the top?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the light in this image come from the top?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the light in this image come from the top?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 305:  20%|▏| 306/1495 [01:42<
[Running Accuracy]: 0.7908,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 306:  20%|▏| 306/1495 [01:42<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from the top?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurry due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurry due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7908,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 306:  21%|▏| 307/1495 [01:42<05:
[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 307:  21%|▏| 307/1495 [01:42<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurry due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this picture?
A. Bushes
B. Lotus flower
C. Pond
D. Wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of this picture?
A. Bushes
B. Lotus flower
C. Pond
D. Wall
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this picture?\nA. Bushes\nB. Lotus flower\nC. Pond\nD. Wall\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 307:  21%|▏| 308/1495 [01:43<09:
[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Lotus flower, , [Prog]: 308:  21%|▏| 308/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this picture?\nA. Bushes\nB. Lotus flower\nC. Pond\nD. Wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Lotus flower, , [Prog]: 308:  21%|▏| 309/1495 [
[Running Accuracy]: 0.7929,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 309:  21%|▏| 309/1495 [01:44<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7929,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 309:  21%|▏| 310/1495 [01:44<07
[Running Accuracy]: 0.7903,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 310:  21%|▏| 310/1495 [01:44<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7903,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 310:  21%|▏| 311/1495 [01:44<06:
[Running Accuracy]: 0.7910,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 311:  21%|▏| 311/1495 [01:44<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?
A. Overexposure
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does this image not have?
A. Overexposure
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does this image not have?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7910,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 311:  21%|▏| 312/1495 [01:45<06
[Running Accuracy]: 0.7917,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 312:  21%|▏| 312/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the aluminum foil on the person's face clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the aluminum foil on the person's face clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the aluminum foil on the person's face clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7917,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 312:  21%|▏| 313/1495 
[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 313:  21%|▏| 313/1495 [01:45<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the aluminum foil on the person's face clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the main focus?
A. Wood
B. Woman
C. Stone wall
D. Rope
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the main focus?
A. Wood
B. Woman
C. Stone wall
D. Rope
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the main focus?\nA. Wood\nB. Woman\nC. Stone wall\nD. Rope\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 313:  21%|▏| 314/1495 [01:45<06:
[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 314:  21%|▏| 314/1495 [01:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the main focus?\nA. Wood\nB. Woman\nC. Stone wall\nD. Rope\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced for the apple in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced for the apple in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced for the apple in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 314:  21%|▏| 315/1495 [01:45<0
[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 315:  21%|▏| 315/1495 [01:45<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced for the apple in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have repetitive patterns?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have repetitive patterns?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 315:  21%|▏| 316/1495 [01:46<05:
[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 316:  21%|▏| 316/1495 [01:46<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man playing the violin emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man playing the violin emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man playing the violin emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 316:  21%|▏| 317/1495 [01:46<05:
[Running Accuracy]: 0.7918,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 317:  21%|▏| 317/1495 [01:46<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man playing the violin emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image in the picture is the focus?
A. Blanket
B. Bed
C. Chair
D. Woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image in the picture is the focus?
A. Blanket
B. Bed
C. Chair
D. Woman
Answer with the option's letter from the given choices directly.

prompts: [["Which image in the picture is the focus?\nA. Blanket\nB. Bed\nC. Chair\nD. Woman\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7918,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 317:  21%|▏| 318/1495 [01:46<05:
[Running Accuracy]: 0.7925,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 318:  21%|▏| 318/1495 [01:46<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image in the picture is the focus?\nA. Blanket\nB. Bed\nC. Chair\nD. Woman\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7925,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 318:  21%|▏| 319/1495 [01:47<0
[Running Accuracy]: 0.7931,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 319:  21%|▏| 319/1495 [01:47<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this picture not have?
A. Underexposure
B. Overexposure
C. Noise
D. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does this picture not have?
A. Underexposure
B. Overexposure
C. Noise
D. Blur
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does this picture not have?\nA. Underexposure\nB. Overexposure\nC. Noise\nD. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7931,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 319:  21%|▏| 320/1495 [01:47<06
[Running Accuracy]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 320:  21%|▏| 320/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this picture not have?\nA. Underexposure\nB. Overexposure\nC. Noise\nD. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 320:  21%|▏| 321/1495 [
[Running Accuracy]: 0.7882,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 321:  21%|▏| 321/1495 [01:47<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the trees in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the trees in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the trees in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7882,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 321:  22%|▏| 322/1495 [01:48<05
[Running Accuracy]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 322:  22%|▏| 322/1495 [01:48<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the trees in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion in this image?
A. Obstruct by snow
B. Too dark to see details
C. Blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion in this image?
A. Obstruct by snow
B. Too dark to see details
C. Blurred
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion in this image?\nA. Obstruct by snow\nB. Too dark to see details\nC. Blurred\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 322:  22%|▏| 323/1495 [01:48<06
[Running Accuracy]: 0.7895,[Response]: A.<|endoftext|>, [Correct Ans]: Obstruct by snow, , [Prog]: 323:  22%|▏| 323/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion in this image?\nA. Obstruct by snow\nB. Too dark to see details\nC. Blurred\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?
A. Clear
B. Moderate
C. Blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Clear
B. Moderate
C. Blurred
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Clear\nB. Moderate\nC. Blurred\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7895,[Response]: A.<|endoftext|>, [Correct Ans]: Obstruct by snow, , [Prog]: 323:  22%|▏| 324/14
[Running Accuracy]: 0.7870,[Response]: B.<|endoftext|>, [Correct Ans]: Blurred, , [Prog]: 324:  22%|▏| 324/1495 [01:48
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?\nA. Clear\nB. Moderate\nC. Blurred\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?
A. Woman's head
B. Feathers
C. Flowers
D. Woman's body
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focus?
A. Woman's head
B. Feathers
C. Flowers
D. Woman's body
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focus?\nA. Woman's head\nB. Feathers\nC. Flowers\nD. Woman's body\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7870,[Response]: B.<|endoftext|>, [Correct Ans]: Blurred, , [Prog]: 324:  22%|▏| 325/1495 [01:48
[Running Accuracy]: 0.7877,[Response]: D.<|endoftext|>, [Correct Ans]: Woman's body, , [Prog]: 325:  22%|▏| 325/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?\nA. Woman's head\nB. Feathers\nC. Flowers\nD. Woman's body\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the fur of the cat?
A. Excellent
B. Bad
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the fur of the cat?
A. Excellent
B. Bad
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the fur of the cat?\nA. Excellent\nB. Bad\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7877,[Response]: D.<|endoftext|>, [Correct Ans]: Woman's body, , [Prog]: 325:  22%|▏| 326/1495 [
[Running Accuracy]: 0.7883,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 326:  22%|▏| 326/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the fur of the cat?\nA. Excellent\nB. Bad\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography technique is used to emphasize the flower in the center?
A. Motion Blur
B. Shallow Depth-of-Field
C. Black and White
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What photography technique is used to emphasize the flower in the center?
A. Motion Blur
B. Shallow Depth-of-Field
C. Black and White
Answer with the option's letter from the given choices directly.

prompts: [["What photography technique is used to emphasize the flower in the center?\nA. Motion Blur\nB. Shallow Depth-of-Field\nC. Black and White\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7883,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 326:  22%|▏| 327/1495 [01
[Running Accuracy]: 0.7890,[Response]: B.<|endoftext|>, [Correct Ans]: Shallow Depth-of-Field, , [Prog]: 327:  22%|▏| 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography technique is used to emphasize the flower in the center?\nA. Motion Blur\nB. Shallow Depth-of-Field\nC. Black and White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any color fringes in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any color fringes in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there any color fringes in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7890,[Response]: B.<|endoftext|>, [Correct Ans]: Shallow Depth-of-Field, , [Prog]: 327:  22%|▏| 
[Running Accuracy]: 0.7896,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 328:  22%|▏| 328/1495 [01:49<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any color fringes in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of zebras in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of zebras in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of zebras in this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7896,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 328:  22%|▏| 329/1495 [01:50<05:
[Running Accuracy]: 0.7903,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 329:  22%|▏| 329/1495 [01:50<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of zebras in this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the human in this image?
A. Over-exposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the human in this image?
A. Over-exposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the human in this image?\nA. Over-exposure\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7903,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 329:  22%|▏| 330/1495 [01:50<
[Running Accuracy]: 0.7909,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 330:  22%|▏| 330/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the human in this image?\nA. Over-exposure\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7909,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 330:  22%|▏| 331/1495 [0
[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 331:  22%|▏| 331/1495 [01:50<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness in this image?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness in this image?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness in this image?\nA. Just fine\nB. Too dark\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 331:  22%|▏| 332/1495 [01:51<05
[Running Accuracy]: 0.7892,[Response]: A.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 332:  22%|▏| 332/1495 [01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness in this image?\nA. Just fine\nB. Too dark\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image make you feel uncomfortable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image make you feel uncomfortable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image make you feel uncomfortable?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7892,[Response]: A.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 332:  22%|▏| 333/1495 [01
[Running Accuracy]: 0.7898,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 333:  22%|▏| 333/1495 [01:51<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image make you feel uncomfortable?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of the wine glass in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of the wine glass in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of the wine glass in this image?\nA. Medium\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7898,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 333:  22%|▏| 334/1495 [01:51<05:
[Running Accuracy]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 334:  22%|▏| 334/1495 [01:51<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of the wine glass in this image?\nA. Medium\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the composition of this image use symmetrical style?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the composition of this image use symmetrical style?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the composition of this image use symmetrical style?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 334:  22%|▏| 335/1495 [01:51<05
[Running Accuracy]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 335:  22%|▏| 335/1495 [01:51<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the composition of this image use symmetrical style?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?
A. Red
B. White
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. Red
B. White
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. Red\nB. White\nC. Yellow\nD. Brown\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 335:  22%|▏| 336/1495 [01:52<05:
[Running Accuracy]: 0.7887,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 336:  22%|▏| 336/1495 [01:52<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?\nA. Red\nB. White\nC. Yellow\nD. Brown\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7887,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 336:  23%|▏| 337/1495 [01:52<05:
[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 337:  23%|▏| 337/1495 [01:52<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any blur in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any blur in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 337:  23%|▏| 338/1495 [01:52<05:
[Running Accuracy]: 0.7870,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 338:  23%|▏| 338/1495 [01:52<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual perception?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a dark visual perception?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark visual perception?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7870,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 338:  23%|▏| 339/1495 [01:53<05:
[Running Accuracy]: 0.7876,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 339:  23%|▏| 339/1495 [01:53<05:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual perception?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stool in focus in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the stool in focus in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the stool in focus in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7876,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 339:  23%|▏| 340/1495 [01:53<05:4
[Running Accuracy]: 0.7853,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 340:  23%|▏| 340/1495 [01:53<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stool in focus in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the clearest?
A. The person's clothes
B. The head of the person
C. The person's hand
D. The person's hair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the clearest?
A. The person's clothes
B. The head of the person
C. The person's hand
D. The person's hair
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the clearest?\nA. The person's clothes\nB. The head of the person\nC. The person's hand\nD. The person's hair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7853,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 340:  23%|▏| 341/1495 [01:53<05:4
[Running Accuracy]: 0.7859,[Response]: B.<|endoftext|>, [Correct Ans]: The head of the person, , [Prog]: 341:  23%|▏| 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the clearest?\nA. The person's clothes\nB. The head of the person\nC. The person's hand\nD. The person's hair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vivid?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image vivid?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vivid?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7859,[Response]: B.<|endoftext|>, [Correct Ans]: The head of the person, , [Prog]: 341:  23%|▏| 
[Running Accuracy]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 342:  23%|▏| 342/1495 [01:54<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vivid?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object or part of the image is the focus?
A. Bed
B. Blanket
C. Clothes
D. Child
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object or part of the image is the focus?
A. Bed
B. Blanket
C. Clothes
D. Child
Answer with the option's letter from the given choices directly.

prompts: [["Which object or part of the image is the focus?\nA. Bed\nB. Blanket\nC. Clothes\nD. Child\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 342:  23%|▏| 343/1495 [01:54<05:
[Running Accuracy]: 0.7843,[Response]: D.<|endoftext|>, [Correct Ans]: Child, , [Prog]: 343:  23%|▏| 343/1495 [01:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object or part of the image is the focus?\nA. Bed\nB. Blanket\nC. Clothes\nD. Child\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the background of this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is the background of this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the background of this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7843,[Response]: D.<|endoftext|>, [Correct Ans]: Child, , [Prog]: 343:  23%|▏| 344/1495 [01:54<0
[Running Accuracy]: 0.7849,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 344:  23%|▏| 344/1495 [01:54<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the background of this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the wall on the left?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall brightness of the wall on the left?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall brightness of the wall on the left?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7849,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 344:  23%|▏| 345/1495 [01:55<07
[Running Accuracy]: 0.7855,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 345:  23%|▏| 345/1495 [01:55<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the wall on the left?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the most clear for the dog?
A. Tail
B. Legs
C. Body
D. Face
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the most clear for the dog?
A. Tail
B. Legs
C. Body
D. Face
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the most clear for the dog?\nA. Tail\nB. Legs\nC. Body\nD. Face\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7855,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 345:  23%|▏| 346/1495 [01:55<06:
[Running Accuracy]: 0.7861,[Response]: D.<|endoftext|>, [Correct Ans]: Face, , [Prog]: 346:  23%|▏| 346/1495 [01:55<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the most clear for the dog?\nA. Tail\nB. Legs\nC. Body\nD. Face\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Dose the wall contain repetitive patterns in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Dose the wall contain repetitive patterns in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Dose the wall contain repetitive patterns in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7861,[Response]: D.<|endoftext|>, [Correct Ans]: Face, , [Prog]: 346:  23%|▏| 347/1495 [01:55<06
[Running Accuracy]: 0.7867,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 347:  23%|▏| 347/1495 [01:55<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Dose the wall contain repetitive patterns in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers in the image?
A. Moderate
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the flowers in the image?
A. Moderate
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the flowers in the image?\nA. Moderate\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7867,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 347:  23%|▏| 348/1495 [01:56<06:
[Running Accuracy]: 0.7845,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 348:  23%|▏| 348/1495 [01:56<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers in the image?\nA. Moderate\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness level of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness level of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness level of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7845,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 348:  23%|▏| 349/1495 [01:56<06
[Running Accuracy]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 349:  23%|▏| 349/1495 [01:56<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness level of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 349:  23%|▏| 350/1495 [01:56<05:
[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 350:  23%|▏| 350/1495 [01:56<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?
A. Computer-generated
B. photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic or computer-generated?
A. Computer-generated
B. photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic or computer-generated?\nA. Computer-generated\nB. photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7857,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 350:  23%|▏| 351/1495 [01:57<06
[Running Accuracy]: 0.7863,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 351:  23%|▏| 351/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?\nA. Computer-generated\nB. photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the Christmas tree the focus in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the Christmas tree the focus in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the Christmas tree the focus in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7863,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 351:  24%|▏| 352/
[Running Accuracy]: 0.7869,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 352:  24%|▏| 352/1495 [01:57<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the Christmas tree the focus in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the main color tone of the person in the image is blue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the main color tone of the person in the image is blue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the main color tone of the person in the image is blue?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7869,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 352:  24%|▏| 353/1495 [01:57<05:
[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 353:  24%|▏| 353/1495 [01:57<05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the main color tone of the person in the image is blue?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest thing in the image?
A. Seaweed
B. Reef
C. Fish tank
D. Fish
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest thing in the image?
A. Seaweed
B. Reef
C. Fish tank
D. Fish
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest thing in the image?\nA. Seaweed\nB. Reef\nC. Fish tank\nD. Fish\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 353:  24%|▏| 354/1495 [01:57<05:5
[Running Accuracy]: 0.7881,[Response]: D.<|endoftext|>, [Correct Ans]: Fish, , [Prog]: 354:  24%|▏| 354/1495 [01:57<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest thing in the image?\nA. Seaweed\nB. Reef\nC. Fish tank\nD. Fish\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is more blurry?
A. The left
B. The right
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is more blurry?
A. The left
B. The right
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is more blurry?\nA. The left\nB. The right\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7881,[Response]: D.<|endoftext|>, [Correct Ans]: Fish, , [Prog]: 354:  24%|▏| 355/1495 [01:58<07
[Running Accuracy]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: The left, , [Prog]: 355:  24%|▏| 355/1495 [01:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is more blurry?\nA. The left\nB. The right\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the man's face?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the man's face?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the man's face?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: The left, , [Prog]: 355:  24%|▏| 356/1495 [01:5
[Running Accuracy]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 356:  24%|▏| 356/1495 [01:58<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the man's face?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall brightness of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall brightness of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 356:  24%|▏| 357/1495 [01:59<06
[Running Accuracy]: 0.7899,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 357:  24%|▏| 357/1495 [01:59<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7899,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 357:  24%|▏| 358/1495 [01:59<06
[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 358:  24%|▏| 358/1495 [01:59<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clock rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clock rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the clock rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 358:  24%|▏| 359/1495 [01:59<06:
[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 359:  24%|▏| 359/1495 [01:59<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clock rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main contribution of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main contribution of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main contribution of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 359:  24%|▏| 360/1495 [02:00<07:
[Running Accuracy]: 0.7917,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 360:  24%|▏| 360/1495 [02:00<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main contribution of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look faded?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look faded?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look faded?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7917,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 360:  24%|▏| 361/1495 [02:00<07
[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 361:  24%|▏| 361/1495 [02:00<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look faded?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main problem in this image that makes it less attractive?
A. Lack of color
B. Low contrast
C. Low brightness
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main problem in this image that makes it less attractive?
A. Lack of color
B. Low contrast
C. Low brightness
Answer with the option's letter from the given choices directly.

prompts: [["What is the main problem in this image that makes it less attractive?\nA. Lack of color\nB. Low contrast\nC. Low brightness\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 361:  24%|▏| 362/1495 [02:00<06:
[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Low brightness, , [Prog]: 362:  24%|▏| 362/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main problem in this image that makes it less attractive?\nA. Lack of color\nB. Low contrast\nC. Low brightness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest object in this picture?
A. Sky
B. Buildings
C. Trees
D. Grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the darkest object in this picture?
A. Sky
B. Buildings
C. Trees
D. Grass
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest object in this picture?\nA. Sky\nB. Buildings\nC. Trees\nD. Grass\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Low brightness, , [Prog]: 362:  24%|▏| 363/1495
[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 363:  24%|▏| 363/1495 [02:01<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest object in this picture?\nA. Sky\nB. Buildings\nC. Trees\nD. Grass\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the frog fully visible, partly visible, or not visible?
A. Not visible
B. Partly visible
C. Fully visible
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the frog fully visible, partly visible, or not visible?
A. Not visible
B. Partly visible
C. Fully visible
Answer with the option's letter from the given choices directly.

prompts: [["Is the frog fully visible, partly visible, or not visible?\nA. Not visible\nB. Partly visible\nC. Fully visible\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 363:  24%|▏| 364/1495 [02:01<0
[Running Accuracy]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Partly visible, , [Prog]: 364:  24%|▏| 364/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the frog fully visible, partly visible, or not visible?\nA. Not visible\nB. Partly visible\nC. Fully visible\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Noise
B. Blur
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Noise
B. Blur
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Noise\nB. Blur\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Partly visible, , [Prog]: 364:  24%|▏| 365/1495
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 365:  24%|▏| 365/1495 [02:02<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Noise\nB. Blur\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 365:  24%|▏| 366/1495 [02:02<0
[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 366:  24%|▏| 366/1495 [02:02<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the leaves in the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the leaves in the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the leaves in the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 366:  25%|▏| 367/1495 [02:02<06:
[Running Accuracy]: 0.7929,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 367:  25%|▏| 367/1495 [02:02<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the leaves in the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an overexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an overexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an overexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7929,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 367:  25%|▏| 368/1495 [02:03<06
[Running Accuracy]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 368:  25%|▏| 368/1495 [02:03<06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an overexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the focus of this image?
A. The snow ground
B. The trees in the backgroud
C. The humans
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the focus of this image?
A. The snow ground
B. The trees in the backgroud
C. The humans
Answer with the option's letter from the given choices directly.

prompts: [["What is the focus of this image?\nA. The snow ground\nB. The trees in the backgroud\nC. The humans\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 368:  25%|▏| 369/1495 [02:03<06:0
[Running Accuracy]: 0.7940,[Response]: C.<|endoftext|>, [Correct Ans]: The humans, , [Prog]: 369:  25%|▏| 369/1495 [02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the focus of this image?\nA. The snow ground\nB. The trees in the backgroud\nC. The humans\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7940,[Response]: C.<|endoftext|>, [Correct Ans]: The humans, , [Prog]: 369:  25%|▏| 370/1495 [02
[Running Accuracy]: 0.7946,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 370:  25%|▏| 370/1495 [02:03<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?
A. Overexposure
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in this picture?
A. Overexposure
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in this picture?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7946,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 370:  25%|▏| 371/1495 [02:04<06
[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 371:  25%|▏| 371/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?\nA. Overexposure\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting of this statue good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting of this statue good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting of this statue good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7925,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 371:  25%|▏| 372/1495 [
[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 372:  25%|▏| 372/1495 [02:04<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting of this statue good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the text in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the text in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the text in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 372:  25%|▏| 373/1495 [02:04<07:
[Running Accuracy]: 0.7936,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 373:  25%|▏| 373/1495 [02:04<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the text in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7936,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 373:  25%|▎| 374/1495 [02:05<06:
[Running Accuracy]: 0.7941,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 374:  25%|▎| 374/1495 [02:05<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is most severe in the image?
A. Overexposure
B. Underexposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion is most severe in the image?
A. Overexposure
B. Underexposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion is most severe in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7941,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 374:  25%|▎| 375/1495 [02:05<08:
[Running Accuracy]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 375:  25%|▎| 375/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is most severe in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the humans in this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the humans in this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the humans in this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 375:  25%|▎| 376/1495 [
[Running Accuracy]: 0.7952,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 376:  25%|▎| 376/1495 [02:06<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the humans in this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Low light
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Low light
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Low light\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7952,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 376:  25%|▎| 377/1495 [02:07<09
[Running Accuracy]: 0.7958,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 377:  25%|▎| 377/1495 [02:07<09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Low light\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the saturation of the woman's clothing in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the saturation of the woman's clothing in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["What is the saturation of the woman's clothing in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7958,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 377:  25%|▎| 378/1495 [02:07<08
[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 378:  25%|▎| 378/1495 [02:07<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the saturation of the woman's clothing in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does this photo have?
A. Noise
B. Blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality issue does this photo have?
A. Noise
B. Blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue does this photo have?\nA. Noise\nB. Blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 378:  25%|▎| 379/1495 [02:07<07
[Running Accuracy]: 0.7968,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 379:  25%|▎| 379/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does this photo have?\nA. Noise\nB. Blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7968,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 379:  25%|▎| 380/1495 
[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 380:  25%|▎| 380/1495 [02:08<07:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Would you say the composition in this image is good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Would you say the composition in this image is good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 380:  25%|▎| 381/1495 [02:08<07:0
[Running Accuracy]: 0.7979,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 381:  25%|▎| 381/1495 [02:08<07:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in the image?
A. Noise
B. Motion blur
C. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality problems does not exist in the image?
A. Noise
B. Motion blur
C. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality problems does not exist in the image?\nA. Noise\nB. Motion blur\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7979,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 381:  26%|▎| 382/1495 [02:08<06:3
[Running Accuracy]: 0.7958,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 382:  26%|▎| 382/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in the image?\nA. Noise\nB. Motion blur\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7958,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 382:  26%|▎| 383/1495 [0
[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 383:  26%|▎| 383/1495 [02:08<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the overall color of the image harmonious?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the overall color of the image harmonious?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the overall color of the image harmonious?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7963,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 383:  26%|▎| 384/1495 [02:09<06
[Running Accuracy]: 0.7969,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 384:  26%|▎| 384/1495 [02:09<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the overall color of the image harmonious?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7969,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 384:  26%|▎| 385/1495 [02:09<06:
[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 385:  26%|▎| 385/1495 [02:09<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 385:  26%|▎| 386/1495 [02:09<06:
[Running Accuracy]: 0.7979,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 386:  26%|▎| 386/1495 [02:09<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7979,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 386:  26%|▎| 387/1495 [02:10<06:
[Running Accuracy]: 0.7984,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 387:  26%|▎| 387/1495 [02:10<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man wearing a black suit emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man wearing a black suit emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the man wearing a black suit emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7984,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 387:  26%|▎| 388/1495 [02:10<05:
[Running Accuracy]: 0.7990,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 388:  26%|▎| 388/1495 [02:10<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man wearing a black suit emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is most apparent distortion in this image?
A. Noise
B. Motion blur
C. Low contrast
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is most apparent distortion in this image?
A. Noise
B. Motion blur
C. Low contrast
Answer with the option's letter from the given choices directly.

prompts: [["What is most apparent distortion in this image?\nA. Noise\nB. Motion blur\nC. Low contrast\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7990,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 388:  26%|▎| 389/1495 [02:11<06:
[Running Accuracy]: 0.7995,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 389:  26%|▎| 389/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is most apparent distortion in this image?\nA. Noise\nB. Motion blur\nC. Low contrast\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure level of the image?
A. Overexposed
B. Underexposed
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure level of the image?
A. Overexposed
B. Underexposed
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure level of the image?\nA. Overexposed\nB. Underexposed\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7995,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 389:  26%|▎| 390/1495 [0
[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 390:  26%|▎| 390/1495 [02:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure level of the image?\nA. Overexposed\nB. Underexposed\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7974,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 390:  26%|▎| 391/1495 [02:1
[Running Accuracy]: 0.7980,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 391:  26%|▎| 391/1495 [02:12<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus of this picture?
A. Center
B. Surrounding
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Center
B. Surrounding
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Center\nB. Surrounding\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7980,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 391:  26%|▎| 392/1495 [02:12<07:
[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 392:  26%|▎| 392/1495 [02:12<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus of this picture?\nA. Center\nB. Surrounding\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there too much noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there too much noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there too much noise in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 392:  26%|▎| 393/1495 [02:12<
[Running Accuracy]: 0.7990,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 393:  26%|▎| 393/1495 [02:12<06:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there too much noise in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the bird in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the bird in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the bird in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7990,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 393:  26%|▎| 394/1495 [02:12<06:3
[Running Accuracy]: 0.7970,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 394:  26%|▎| 394/1495 [02:12<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the bird in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the women the brightest part in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the women the brightest part in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the women the brightest part in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7970,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 394:  26%|▎| 395/1495 [02:13<06
[Running Accuracy]: 0.7975,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 395:  26%|▎| 395/1495 [02:13<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the women the brightest part in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of feeling does the image give?
A. Restless
B. Depressing
C. Melancholy
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does the image give?
A. Restless
B. Depressing
C. Melancholy
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does the image give?\nA. Restless\nB. Depressing\nC. Melancholy\nD. Fresh\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7975,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 395:  26%|▎| 396/1495 [02:13<06:
[Running Accuracy]: 0.7980,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 396:  26%|▎| 396/1495 [02:13<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of feeling does the image give?\nA. Restless\nB. Depressing\nC. Melancholy\nD. Fresh\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the color of the flags hanging above the door in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the color of the flags hanging above the door in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the color of the flags hanging above the door in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7980,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 396:  27%|▎| 397/1495 [02:13<0
[Running Accuracy]: 0.7985,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 397:  27%|▎| 397/1495 [02:13<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the color of the flags hanging above the door in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7985,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 397:  27%|▎| 398/1495 [02:14<05:
[Running Accuracy]: 0.7990,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 398:  27%|▎| 398/1495 [02:14<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?
A. Dark
B. Bright
C. Fresh
D. Happy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the image give?
A. Dark
B. Bright
C. Fresh
D. Happy
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the image give?\nA. Dark\nB. Bright\nC. Fresh\nD. Happy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7990,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 398:  27%|▎| 399/1495 [02:14<
[Running Accuracy]: 0.7970,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 399:  27%|▎| 399/1495 [02:14<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?\nA. Dark\nB. Bright\nC. Fresh\nD. Happy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters in the image clear?
A. Unclear
B. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters in the image clear?
A. Unclear
B. Clear
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters in the image clear?\nA. Unclear\nB. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7970,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 399:  27%|▎| 400/1495 [02:14<05
[Running Accuracy]: 0.7975,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 400:  27%|▎| 400/1495 [02:14<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters in the image clear?\nA. Unclear\nB. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two girls in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two girls in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the two girls in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7975,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 400:  27%|▎| 401/1495 [02:15<0
[Running Accuracy]: 0.7980,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 401:  27%|▎| 401/1495 [02:15<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two girls in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Overexposure
B. Underexposure
C. Noise
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Overexposure
B. Underexposure
C. Noise
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7980,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 401:  27%|▎| 402/1495 [02:15<07:
[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 402:  27%|▎| 402/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Very blurry
B. Slightly blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Very blurry
B. Slightly blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Very blurry\nB. Slightly blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7985,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 402:  27%|▎| 403/1495 [
[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 403:  27%|▎| 403/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Very blurry\nB. Slightly blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe quality issue in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe quality issue in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe quality issue in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 403:  27%|▎| 404/149
[Running Accuracy]: 0.7995,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 404:  27%|▎| 404/1495 [02:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe quality issue in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast in this image?
A. Medium contrast
B. High contrast
C. Low contrast
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast in this image?
A. Medium contrast
B. High contrast
C. Low contrast
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast in this image?\nA. Medium contrast\nB. High contrast\nC. Low contrast\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7995,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 404:  27%|▎| 405/1495 [02:16<0
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: High contrast, , [Prog]: 405:  27%|▎| 405/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast in this image?\nA. Medium contrast\nB. High contrast\nC. Low contrast\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Underexposure\nB. Motion blur\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: High contrast, , [Prog]: 405:  27%|▎| 406/1495 
[Running Accuracy]: 0.8005,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 406:  27%|▎| 406/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Underexposure\nB. Motion blur\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall clarity of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall clarity of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8005,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 406:  27%|▎| 407/1495 [
[Running Accuracy]: 0.7985,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 407:  27%|▎| 407/1495 [02:17<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Noise
B. Motion blur
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Noise
B. Motion blur
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Noise\nB. Motion blur\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7985,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 407:  27%|▎| 408/1495 [02:18<
[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 408:  27%|▎| 408/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Noise\nB. Motion blur\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is highlighted as subject?
A. The bench
B. The garbage can
C. The sheep
D. Nothing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is highlighted as subject?
A. The bench
B. The garbage can
C. The sheep
D. Nothing
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is highlighted as subject?\nA. The bench\nB. The garbage can\nC. The sheep\nD. Nothing\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 408:  27%|▎| 409/1495 [0
[Running Accuracy]: 0.7995,[Response]: C.<|endoftext|>, [Correct Ans]: The sheep, , [Prog]: 409:  27%|▎| 409/1495 [02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is highlighted as subject?\nA. The bench\nB. The garbage can\nC. The sheep\nD. Nothing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the flowers in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the flowers in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7995,[Response]: C.<|endoftext|>, [Correct Ans]: The sheep, , [Prog]: 409:  27%|▎| 410/1495 [02:
[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 410:  27%|▎| 410/1495 [02:18<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the hat on the little boy in the picture?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the hat on the little boy in the picture?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the hat on the little boy in the picture?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 410:  27%|▎| 411/1495 [02:18<06:
[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 411:  27%|▎| 411/1495 [02:18<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the hat on the little boy in the picture?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there recurring patterns in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there recurring patterns in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 411:  28%|▎| 412/1495 [02:19<06
[Running Accuracy]: 0.8010,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 412:  28%|▎| 412/1495 [02:19<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Normal
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Normal
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Normal\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8010,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 412:  28%|▎| 413/1495 [02:19<06:
[Running Accuracy]: 0.8015,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 413:  28%|▎| 413/1495 [02:19<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Normal\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the building in this image?
A. Blur
B. Noise
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the building in this image?
A. Blur
B. Noise
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the building in this image?\nA. Blur\nB. Noise\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8015,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 413:  28%|▎| 414/1495 [02:20<
[Running Accuracy]: 0.8019,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 414:  28%|▎| 414/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the building in this image?\nA. Blur\nB. Noise\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in the image?
A. Motion blur
B. Overexposure
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does not exist in the image?
A. Motion blur
B. Overexposure
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does not exist in the image?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8019,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 414:  28%|▎| 415/1495
[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 415:  28%|▎| 415/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in the image?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?
A. Bad
B. Good
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus in this image?
A. Bad
B. Good
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus in this image?\nA. Bad\nB. Good\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8000,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 415:  28%|▎| 416/1495 [0
[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 416:  28%|▎| 416/1495 [02:21<07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?\nA. Bad\nB. Good\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?
A. Cyan
B. White
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. Cyan
B. White
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. Cyan\nB. White\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 416:  28%|▎| 417/1495 [02:21<06
[Running Accuracy]: 0.7986,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 417:  28%|▎| 417/1495 [02:21<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?\nA. Cyan\nB. White\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this man in the image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this man in the image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this man in the image?\nA. Bright\nB. Dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7986,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 417:  28%|▎| 418/1495 [02:21<0
[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 418:  28%|▎| 418/1495 [02:21<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this man in the image?\nA. Bright\nB. Dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color in the image?
A. Monotonous
B. Moderate
C. Abundant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color in the image?
A. Monotonous
B. Moderate
C. Abundant
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color in the image?\nA. Monotonous\nB. Moderate\nC. Abundant\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7990,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 418:  28%|▎| 419/1495 [02:21<06
[Running Accuracy]: 0.7971,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 419:  28%|▎| 419/1495 [02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color in the image?\nA. Monotonous\nB. Moderate\nC. Abundant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image's color saturation high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image's color saturation high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image's color saturation high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7971,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 419:  28%|▎| 420/1495 [02
[Running Accuracy]: 0.7976,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 420:  28%|▎| 420/1495 [02:22<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image's color saturation high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. Square stone
B. Bicycle
C. Vegetation
D. Street lamp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. Square stone
B. Bicycle
C. Vegetation
D. Street lamp
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. Square stone\nB. Bicycle\nC. Vegetation\nD. Street lamp\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7976,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 420:  28%|▎| 421/1495 [02:22<05:
[Running Accuracy]: 0.7981,[Response]: A.<|endoftext|>, [Correct Ans]: Square stone, , [Prog]: 421:  28%|▎| 421/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. Square stone\nB. Bicycle\nC. Vegetation\nD. Street lamp\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees in this image in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the trees in this image in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the trees in this image in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7981,[Response]: A.<|endoftext|>, [Correct Ans]: Square stone, , [Prog]: 421:  28%|▎| 422/1495 [
[Running Accuracy]: 0.7986,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 422:  28%|▎| 422/1495 [02:23<07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees in this image in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7986,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 422:  28%|▎| 423/1495 [02:23<06:5
[Running Accuracy]: 0.7991,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 423:  28%|▎| 423/1495 [02:23<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the extent of blurriness in the green plants in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the extent of blurriness in the green plants in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["What is the extent of blurriness in the green plants in this image?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7991,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 423:  28%|▎| 424/1495 [02:23<06
[Running Accuracy]: 0.7995,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 424:  28%|▎| 424/1495 [02:23<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the extent of blurriness in the green plants in this image?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this image?
A. Underexposure
B. Compression Artifacts
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this image?
A. Underexposure
B. Compression Artifacts
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this image?\nA. Underexposure\nB. Compression Artifacts\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7995,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 424:  28%|▎| 425/1495 [02:24<
[Running Accuracy]: 0.8000,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 425:  28%|▎| 425/1495 [02:24<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this image?\nA. Underexposure\nB. Compression Artifacts\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the composition in this image?
A. Banana tree
B. Basket
C. Old lady
D. Cat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the composition in this image?
A. Banana tree
B. Basket
C. Old lady
D. Cat
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the composition in this image?\nA. Banana tree\nB. Basket\nC. Old lady\nD. Cat\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8000,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 425:  28%|▎| 426/1495 [02:24<0
[Running Accuracy]: 0.8005,[Response]: C.<|endoftext|>, [Correct Ans]: Old lady, , [Prog]: 426:  28%|▎| 426/1495 [02:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the composition in this image?\nA. Banana tree\nB. Basket\nC. Old lady\nD. Cat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8005,[Response]: C.<|endoftext|>, [Correct Ans]: Old lady, , [Prog]: 426:  29%|▎| 427/1495 [02:2
[Running Accuracy]: 0.8009,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 427:  29%|▎| 427/1495 [02:24<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Over-exposure
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Over-exposure
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Over-exposure\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8009,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 427:  29%|▎| 428/1495 [02:24<05:1
[Running Accuracy]: 0.8014,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 428:  29%|▎| 428/1495 [02:24<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Over-exposure\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lower right corner of this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lower right corner of this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lower right corner of this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8014,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 428:  29%|▎| 429/1495 [02:25<0
[Running Accuracy]: 0.7995,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 429:  29%|▎| 429/1495 [02:25<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lower right corner of this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have underexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7995,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 429:  29%|▎| 430/1495 [02:25<05:4
[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 430:  29%|▎| 430/1495 [02:25<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have underexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the statue clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters on the statue clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters on the statue clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 430:  29%|▎| 431/1495 [02:26<07:0
[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 431:  29%|▎| 431/1495 [02:26<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the statue clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the clothes of humans contain rich texture in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the clothes of humans contain rich texture in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the clothes of humans contain rich texture in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8005,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 431:  29%|▎| 432/1495 [02:26<06:
[Running Accuracy]: 0.7986,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 432:  29%|▎| 432/1495 [02:26<06:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the clothes of humans contain rich texture in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dull
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dull
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dull\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7986,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 432:  29%|▎| 433/1495 [02:26<06:1
[Running Accuracy]: 0.7968,[Response]: A.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 433:  29%|▎| 433/1495 [02:26<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dull\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How saturated is the color of the sky in this image?
A. Very blue
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How saturated is the color of the sky in this image?
A. Very blue
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How saturated is the color of the sky in this image?\nA. Very blue\nB. Monotonous\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7968,[Response]: A.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 433:  29%|▎| 434/1495 [02:27<
[Running Accuracy]: 0.7972,[Response]: A.<|endoftext|>, [Correct Ans]: Very blue, , [Prog]: 434:  29%|▎| 434/1495 [02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How saturated is the color of the sky in this image?\nA. Very blue\nB. Monotonous\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Motion blur
B. Noise
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Motion blur
B. Noise
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Motion blur\nB. Noise\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7972,[Response]: A.<|endoftext|>, [Correct Ans]: Very blue, , [Prog]: 434:  29%|▎| 435/1495 [02:
[Running Accuracy]: 0.7954,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 435:  29%|▎| 435/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Motion blur\nB. Noise\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7954,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 435:  29%|▎| 436/1495 [0
[Running Accuracy]: 0.7959,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 436:  29%|▎| 436/1495 [02:28<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the yarn in this photo?
A. Monotonous
B. Vibrant
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the yarn in this photo?
A. Monotonous
B. Vibrant
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the yarn in this photo?\nA. Monotonous\nB. Vibrant\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7959,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 436:  29%|▎| 437/1495 [02:28<06:
[Running Accuracy]: 0.7963,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 437:  29%|▎| 437/1495 [02:28
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the yarn in this photo?\nA. Monotonous\nB. Vibrant\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image has the brightest color?
A. Red wall
B. Holly
C. Grassland
D. Yellow flowers
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image has the brightest color?
A. Red wall
B. Holly
C. Grassland
D. Yellow flowers
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image has the brightest color?\nA. Red wall\nB. Holly\nC. Grassland\nD. Yellow flowers\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7963,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 437:  29%|▎| 438/1495 [02:28
[Running Accuracy]: 0.7968,[Response]: D.<|endoftext|>, [Correct Ans]: Yellow flowers, , [Prog]: 438:  29%|▎| 438/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image has the brightest color?\nA. Red wall\nB. Holly\nC. Grassland\nD. Yellow flowers\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7968,[Response]: D.<|endoftext|>, [Correct Ans]: Yellow flowers, , [Prog]: 438:  29%|▎| 439/1495
[Running Accuracy]: 0.7950,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 439:  29%|▎| 439/1495 [02:29<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color pleasing in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color pleasing in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color pleasing in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7950,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 439:  29%|▎| 440/1495 [02:29<05:
[Running Accuracy]: 0.7955,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 440:  29%|▎| 440/1495 [02:29<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color pleasing in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the ears of the giraffe in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the ears of the giraffe in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the ears of the giraffe in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7955,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 440:  29%|▎| 441/1495 [02:29<05:
[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 441:  29%|▎| 441/1495 [02:29<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the ears of the giraffe in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human face on the left of this image?
A. Dark
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the human face on the left of this image?
A. Dark
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the human face on the left of this image?\nA. Dark\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 441:  30%|▎| 442/1495 [02:29<05:1
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 442:  30%|▎| 442/1495 [02:29<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human face on the left of this image?\nA. Dark\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any severe distortions in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any severe distortions in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there any severe distortions in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 442:  30%|▎| 443/1495 [02:30<05
[Running Accuracy]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 443:  30%|▎| 443/1495 [02:30<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any severe distortions in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?
A. Low light
B. Over-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of this image?
A. Low light
B. Over-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of this image?\nA. Low light\nB. Over-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 443:  30%|▎| 444/1495 [02:30<06:
[Running Accuracy]: 0.7950,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 444:  30%|▎| 444/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of this image?\nA. Low light\nB. Over-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Motion blur
B. Compression
C. Brightness
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Motion blur
B. Compression
C. Brightness
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Motion blur\nB. Compression\nC. Brightness\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7950,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 444:  30%|▎| 445/1495 
[Running Accuracy]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 445:  30%|▎| 445/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Motion blur\nB. Compression\nC. Brightness\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is emphasized in the center?
A. The two girls with backpacks
B. The walking man
C. The building
D. The plants
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is emphasized in the center?
A. The two girls with backpacks
B. The walking man
C. The building
D. The plants
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is emphasized in the center?\nA. The two girls with backpacks\nB. The walking man\nC. The building\nD. The plants\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 445:  30%|▎| 446/1495 [0
[Running Accuracy]: 0.7960,[Response]: A.<|endoftext|>, [Correct Ans]: The two girls with backpacks, , [Prog]: 446:  3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is emphasized in the center?\nA. The two girls with backpacks\nB. The walking man\nC. The building\nD. The plants\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the humans in the image?
A. Noise
B. Motion blur
C. Low light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the humans in the image?
A. Noise
B. Motion blur
C. Low light
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the humans in the image?\nA. Noise\nB. Motion blur\nC. Low light\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7960,[Response]: A.<|endoftext|>, [Correct Ans]: The two girls with backpacks, , [Prog]: 446:  3
[Running Accuracy]: 0.7964,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 447:  30%|▎| 447/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the humans in the image?\nA. Noise\nB. Motion blur\nC. Low light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of the image pyramid-shaped?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of the image pyramid-shaped?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of the image pyramid-shaped?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7964,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 447:  30%|▎| 448/1495 [0
[Running Accuracy]: 0.7946,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 448:  30%|▎| 448/1495 [02:32<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of the image pyramid-shaped?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an underexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7946,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 448:  30%|▎| 449/1495 [02:32<06:
[Running Accuracy]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 449:  30%|▎| 449/1495 [02:32<06:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have artifacts?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have artifacts?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have artifacts?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 449:  30%|▎| 450/1495 [02:32<05:5
[Running Accuracy]: 0.7956,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 450:  30%|▎| 450/1495 [02:32<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have artifacts?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues are present in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality issues are present in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality issues are present in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7956,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 450:  30%|▎| 451/1495 [02:33<05:
[Running Accuracy]: 0.7960,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 451:  30%|▎| 451/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues are present in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light in the image come from?
A. Left
B. Bottom
C. Right
D. Top
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light in the image come from?
A. Left
B. Bottom
C. Right
D. Top
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light in the image come from?\nA. Left\nB. Bottom\nC. Right\nD. Top\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7960,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 451:  30%|▎| 452/1495 [
[Running Accuracy]: 0.7942,[Response]: D.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 452:  30%|▎| 452/1495 [02:33<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light in the image come from?\nA. Left\nB. Bottom\nC. Right\nD. Top\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little girl emphasized in the center in the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little girl emphasized in the center in the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the little girl emphasized in the center in the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7942,[Response]: D.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 452:  30%|▎| 453/1495 [02:33<0
[Running Accuracy]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 453:  30%|▎| 453/1495 [02:33<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little girl emphasized in the center in the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the sky in this image?
A. Noise
B. Under-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the sky in this image?
A. Noise
B. Under-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the sky in this image?\nA. Noise\nB. Under-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 453:  30%|▎| 454/1495 [02:34<05:
[Running Accuracy]: 0.7952,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 454:  30%|▎| 454/1495 [02:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the sky in this image?\nA. Noise\nB. Under-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?
A. Dence
B. Grass
C. Hawk
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Dence
B. Grass
C. Hawk
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Dence\nB. Grass\nC. Hawk\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C. Hawk

[Running Accuracy]: 0.7952,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 454:  30%|▎| 455/1495 [02:34<0
[Running Accuracy]: 0.7956,[Response]: C. Hawk<|endoftext|>, [Correct Ans]: Hawk, , [Prog]: 455:  30%|▎| 455/1495 [02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?\nA. Dence\nB. Grass\nC. Hawk\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C. Hawk<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7956,[Response]: C. Hawk<|endoftext|>, [Correct Ans]: Hawk, , [Prog]: 455:  31%|▎| 456/1495 [02:
[Running Accuracy]: 0.7961,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 456:  31%|▎| 456/1495 [02:34<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the darkest?
A. Chair
B. Man with black hair
C. Mural
D. Man with yellow hair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the darkest?
A. Chair
B. Man with black hair
C. Mural
D. Man with yellow hair
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the darkest?\nA. Chair\nB. Man with black hair\nC. Mural\nD. Man with yellow hair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7961,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 456:  31%|▎| 457/1495 [02:34<05:
[Running Accuracy]: 0.7965,[Response]: A.<|endoftext|>, [Correct Ans]: Chair, , [Prog]: 457:  31%|▎| 457/1495 [02:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the darkest?\nA. Chair\nB. Man with black hair\nC. Mural\nD. Man with yellow hair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the fruit in the image?
A. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the fruit in the image?
A. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the fruit in the image?\nA. Clear\nB. Moderate\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7965,[Response]: A.<|endoftext|>, [Correct Ans]: Chair, , [Prog]: 457:  31%|▎| 458/1495 [02:35<0
[Running Accuracy]: 0.7948,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 458:  31%|▎| 458/1495 [02:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the fruit in the image?\nA. Clear\nB. Moderate\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the rock on the right of the image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the rock on the right of the image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the rock on the right of the image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7948,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 458:  31%|▎| 459/1495 [02:35<
[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 459:  31%|▎| 459/1495 [02:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the rock on the right of the image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the woman in this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the woman in this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the woman in this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 459:  31%|▎| 460/1495 [02:35<
[Running Accuracy]: 0.7957,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 460:  31%|▎| 460/1495 [02:35<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the woman in this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?
A. Medium
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Medium
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Medium\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7957,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 460:  31%|▎| 461/1495 [02:36<05:
[Running Accuracy]: 0.7939,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 461:  31%|▎| 461/1495 [02:36<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?\nA. Medium\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the door wall in the background clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the door wall in the background clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the door wall in the background clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7939,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 461:  31%|▎| 462/1495 [02:36<
[Running Accuracy]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 462:  31%|▎| 462/1495 [02:36<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the door wall in the background clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in this picture?
A. Dirt
B. Butterfly
C. Leaves
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in this picture?
A. Dirt
B. Butterfly
C. Leaves
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in this picture?\nA. Dirt\nB. Butterfly\nC. Leaves\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 462:  31%|▎| 463/1495 [02:36<05:1
[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 463:  31%|▎| 463/1495 [02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in this picture?\nA. Dirt\nB. Butterfly\nC. Leaves\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Noise
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Noise
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Noise\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 463:  31%|▎| 464/1495 [02:
[Running Accuracy]: 0.7953,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 464:  31%|▎| 464/1495 [02:37<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Noise\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Colorful
B. Average
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Average
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Average\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7953,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 464:  31%|▎| 465/1495 [02:37<0
[Running Accuracy]: 0.7957,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 465:  31%|▎| 465/1495 [02:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Colorful\nB. Average\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this image?
A. Brightness
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this image?
A. Brightness
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this image?\nA. Brightness\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7957,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 465:  31%|▎| 466/1495 [02:3
[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 466:  31%|▎| 466/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this image?\nA. Brightness\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?
A. Overexposure
B. Out of focus
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in this picture?
A. Overexposure
B. Out of focus
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in this picture?\nA. Overexposure\nB. Out of focus\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 466:  31%|▎| 467/1495 [0
[Running Accuracy]: 0.7944,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 467:  31%|▎| 467/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?\nA. Overexposure\nB. Out of focus\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues exist in the image?
A. Motion blur
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality issues exist in the image?
A. Motion blur
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality issues exist in the image?\nA. Motion blur\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7944,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 467:  31%|▎| 468/1495 [
[Running Accuracy]: 0.7927,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 468:  31%|▎| 468/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues exist in the image?\nA. Motion blur\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the foliage in this image very blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the foliage in this image very blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the foliage in this image very blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7927,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 468:  31%|▎| 469/1495 [
[Running Accuracy]: 0.7932,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 469:  31%|▎| 469/1495 [02:39<06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the foliage in this image very blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there overexposures from the sky?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there overexposures from the sky?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there overexposures from the sky?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7932,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 469:  31%|▎| 470/1495 [02:39<07:0
[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 470:  31%|▎| 470/1495 [02:39<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there overexposures from the sky?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7915,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 470:  32%|▎| 471/1495 [02:40<06:
[Running Accuracy]: 0.7919,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 471:  32%|▎| 471/1495 [02:40<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7919,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 471:  32%|▎| 472/1495 [02:40<06
[Running Accuracy]: 0.7924,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 472:  32%|▎| 472/1495 [02:40<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7924,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 472:  32%|▎| 473/1495 [02:40<05
[Running Accuracy]: 0.7928,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 473:  32%|▎| 473/1495 [02:40<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is being emphasized in the center of the image composition?
A. People
B. Trees
C. Clouds
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is being emphasized in the center of the image composition?
A. People
B. Trees
C. Clouds
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["What is being emphasized in the center of the image composition?\nA. People\nB. Trees\nC. Clouds\nD. Sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7928,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 473:  32%|▎| 474/1495 [02:40<05:2
[Running Accuracy]: 0.7932,[Response]: A.<|endoftext|>, [Correct Ans]: People, , [Prog]: 474:  32%|▎| 474/1495 [02:40<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is being emphasized in the center of the image composition?\nA. People\nB. Trees\nC. Clouds\nD. Sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color vividity of the image?
A. Totally black and white
B. Faded, not yet black and white
C. Vivid and saturated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color vividity of the image?
A. Totally black and white
B. Faded, not yet black and white
C. Vivid and saturated
Answer with the option's letter from the given choices directly.

prompts: [["How is the color vividity of the image?\nA. Totally black and white\nB. Faded, not yet black and white\nC. Vivid and saturated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7932,[Response]: A.<|endoftext|>, [Correct Ans]: People, , [Prog]: 474:  32%|▎| 475/1495 [02:41<
[Running Accuracy]: 0.7916,[Response]: B.<|endoftext|>, [Correct Ans]: Totally black and white, , [Prog]: 475:  32%|▎|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color vividity of the image?\nA. Totally black and white\nB. Faded, not yet black and white\nC. Vivid and saturated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is present in this image?
A. Noise
B. Overexposure
C. Motion-blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is present in this image?
A. Noise
B. Overexposure
C. Motion-blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is present in this image?\nA. Noise\nB. Overexposure\nC. Motion-blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7916,[Response]: B.<|endoftext|>, [Correct Ans]: Totally black and white, , [Prog]: 475:  32%|▎|
[Running Accuracy]: 0.7920,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 476:  32%|▎| 476/1495 [02:41<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is present in this image?\nA. Noise\nB. Overexposure\nC. Motion-blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting of this image very bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting of this image very bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting of this image very bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7920,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 476:  32%|▎| 477/1495 [02:41<0
[Running Accuracy]: 0.7925,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 477:  32%|▎| 477/1495 [02:41<05:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting of this image very bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the textures in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the textures in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the textures in this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7925,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 477:  32%|▎| 478/1495 [02:42<06:3
[Running Accuracy]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 478:  32%|▎| 478/1495 [02:42<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the textures in this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness of the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness of the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 478:  32%|▎| 479/1495 [02:42<06:
[Running Accuracy]: 0.7933,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 479:  32%|▎| 479/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness does the yellow sign in this image have?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blurriness does the yellow sign in this image have?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blurriness does the yellow sign in this image have?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7933,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 479:  32%|▎| 480/1495 [0
[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 480:  32%|▎| 480/1495 [02:43<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness does the yellow sign in this image have?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 480:  32%|▎| 481/1495 [02:43<
[Running Accuracy]: 0.7942,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 481:  32%|▎| 481/1495 [02:43<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in this picture?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in this picture?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7942,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 481:  32%|▎| 482/1495 [02:43<05:1
[Running Accuracy]: 0.7925,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 482:  32%|▎| 482/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this picture?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the main characters in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the main characters in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the main characters in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7925,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 482:  32%|▎| 483/1495 [
[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 483:  32%|▎| 483/1495 [02:43<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the main characters in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7930,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 483:  32%|▎| 484/1495 [02:44<05:
[Running Accuracy]: 0.7934,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 484:  32%|▎| 484/1495 [02:44<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an underexposure problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7934,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 484:  32%|▎| 485/1495 [02:44<05
[Running Accuracy]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 485:  32%|▎| 485/1495 [02:44<05:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness of the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness of the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 485:  33%|▎| 486/1495 [02:44<05:0
[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 486:  33%|▎| 486/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the egret emphasized in the center of this image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the egret emphasized in the center of this image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the egret emphasized in the center of this image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 486:  33%|▎| 487/1
[Running Accuracy]: 0.7926,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 487:  33%|▎| 487/1495 [02:45<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the egret emphasized in the center of this image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?
A. Very blurry
B. Completely blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness of the image?
A. Very blurry
B. Completely blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness of the image?\nA. Very blurry\nB. Completely blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7926,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 487:  33%|▎| 488/1495 [02:45<05:
[Running Accuracy]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 488:  33%|▎| 488/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?\nA. Very blurry\nB. Completely blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the subject emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the subject emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 488:  33%|▎| 489/149
[Running Accuracy]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 489:  33%|▎| 489/1495 [02:45<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 489:  33%|▎| 490/1495 [02:45<04:
[Running Accuracy]: 0.7939,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 490:  33%|▎| 490/1495 [02:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show strong zoom blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image show strong zoom blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image show strong zoom blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7939,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 490:  33%|▎| 491/1495 [02:46<0
[Running Accuracy]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 491:  33%|▎| 491/1495 [02:46<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show strong zoom blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the rock totally clear, partly clear, or totally blurry?
A. Totally blurry
B. Partly clear
C. Totally clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the rock totally clear, partly clear, or totally blurry?
A. Totally blurry
B. Partly clear
C. Totally clear
Answer with the option's letter from the given choices directly.

prompts: [["Is the rock totally clear, partly clear, or totally blurry?\nA. Totally blurry\nB. Partly clear\nC. Totally clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 491:  33%|▎| 492/1495 [02:46<06:
[Running Accuracy]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Partly clear, , [Prog]: 492:  33%|▎| 492/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the rock totally clear, partly clear, or totally blurry?\nA. Totally blurry\nB. Partly clear\nC. Totally clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus in this picture?
A. Surrounding areas
B. Center
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus in this picture?
A. Surrounding areas
B. Center
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus in this picture?\nA. Surrounding areas\nB. Center\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Partly clear, , [Prog]: 492:  33%|▎| 493/1495 [
[Running Accuracy]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 493:  33%|▎| 493/1495 [02:47<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus in this picture?\nA. Surrounding areas\nB. Center\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What can be said about the bluriness of this image?
A. Accepatable
B. Not blurry
C. Quite blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What can be said about the bluriness of this image?
A. Accepatable
B. Not blurry
C. Quite blurry
Answer with the option's letter from the given choices directly.

prompts: [["What can be said about the bluriness of this image?\nA. Accepatable\nB. Not blurry\nC. Quite blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 493:  33%|▎| 494/1495 [02:47<
[Running Accuracy]: 0.7955,[Response]: C.<|endoftext|>, [Correct Ans]: Quite blurry, , [Prog]: 494:  33%|▎| 494/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What can be said about the bluriness of this image?\nA. Accepatable\nB. Not blurry\nC. Quite blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is not present in this image?
A. Underexposure
B. Overexposure
C. Out-of-Focus
D. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is not present in this image?
A. Underexposure
B. Overexposure
C. Out-of-Focus
D. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is not present in this image?\nA. Underexposure\nB. Overexposure\nC. Out-of-Focus\nD. Motion Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7955,[Response]: C.<|endoftext|>, [Correct Ans]: Quite blurry, , [Prog]: 494:  33%|▎| 495/1495 [
[Running Accuracy]: 0.7960,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 495:  33%|▎| 495/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion is not present in this image?\nA. Underexposure\nB. Overexposure\nC. Out-of-Focus\nD. Motion Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7960,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 495:  33%|▎| 496/1495 
[Running Accuracy]: 0.7964,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 496:  33%|▎| 496/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have clear focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have clear focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have clear focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7964,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 496:  33%|▎| 497/1495 [0
[Running Accuracy]: 0.7968,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 497:  33%|▎| 497/1495 [02:49<08:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have clear focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Person
B. Grassland
C. Sky
D. Mountain
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Person
B. Grassland
C. Sky
D. Mountain
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Person\nB. Grassland\nC. Sky\nD. Mountain\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7968,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 497:  33%|▎| 498/1495 [02:49<08:3
[Running Accuracy]: 0.7972,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 498:  33%|▎| 498/1495 [02:49<08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Person\nB. Grassland\nC. Sky\nD. Mountain\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look like it was taken by a professional camera or a smartphone?
A. Smartphone
B. Professional camera
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look like it was taken by a professional camera or a smartphone?
A. Smartphone
B. Professional camera
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look like it was taken by a professional camera or a smartphone?\nA. Smartphone\nB. Professional camera\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7972,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 498:  33%|▎| 499/1495 [02:50<07:
[Running Accuracy]: 0.7956,[Response]: B.<|endoftext|>, [Correct Ans]: Smartphone, , [Prog]: 499:  33%|▎| 499/1495 [02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look like it was taken by a professional camera or a smartphone?\nA. Smartphone\nB. Professional camera\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the light in this picture?
A. Bright
B. Dim
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is the light in this picture?
A. Bright
B. Dim
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the light in this picture?\nA. Bright\nB. Dim\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7956,[Response]: B.<|endoftext|>, [Correct Ans]: Smartphone, , [Prog]: 499:  33%|▎| 500/1495 [02
[Running Accuracy]: 0.7960,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 500:  33%|▎| 500/1495 [02:50<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the light in this picture?\nA. Bright\nB. Dim\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7960,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 500:  34%|▎| 501/1495 [02:50<06:
[Running Accuracy]: 0.7964,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 501:  34%|▎| 501/1495 [02:50<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pattern and text on the piano clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pattern and text on the piano clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pattern and text on the piano clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7964,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 501:  34%|▎| 502/1495 [02:51<05:
[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 502:  34%|▎| 502/1495 [02:51<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pattern and text on the piano clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues are present in the image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues are present in the image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What issues are present in the image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 502:  34%|▎| 503/1495 [02:51<05:2
[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 503:  34%|▎| 503/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues are present in the image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7952,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 503:  34%|▎| 504/1495 [0
[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 504:  34%|▎| 504/1495 [02:51<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image faded?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image faded?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image faded?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7937,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 504:  34%|▎| 505/1495 [02:51<05:
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 505:  34%|▎| 505/1495 [02:51<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image faded?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blur does the man in this image have?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blur does the man in this image have?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["What level of blur does the man in this image have?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 505:  34%|▎| 506/1495 [02:52<05:
[Running Accuracy]: 0.7945,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 506:  34%|▎| 506/1495 [02:52<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blur does the man in this image have?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7945,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 506:  34%|▎| 507/1495 [02:52<
[Running Accuracy]: 0.7929,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 507:  34%|▎| 507/1495 [02:52<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the most eye-catching in this image?
A. Light blue
B. Gray
C. Green
D. Dark blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the most eye-catching in this image?
A. Light blue
B. Gray
C. Green
D. Dark blue
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the most eye-catching in this image?\nA. Light blue\nB. Gray\nC. Green\nD. Dark blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7929,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 507:  34%|▎| 508/1495 [02:52<
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Dark blue, , [Prog]: 508:  34%|▎| 508/1495 [02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the most eye-catching in this image?\nA. Light blue\nB. Gray\nC. Green\nD. Dark blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show strong contrast?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image show strong contrast?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image show strong contrast?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Dark blue, , [Prog]: 508:  34%|▎| 509/1495 [02:
[Running Accuracy]: 0.7917,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 509:  34%|▎| 509/1495 [02:53<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image show strong contrast?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7917,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 509:  34%|▎| 510/1495 [02:53<04:
[Running Accuracy]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 510:  34%|▎| 510/1495 [02:53<04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the most eye-catching?
A. Fork
B. Cup
C. Birthday cake
D. Person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the most eye-catching?
A. Fork
B. Cup
C. Birthday cake
D. Person
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the most eye-catching?\nA. Fork\nB. Cup\nC. Birthday cake\nD. Person\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 510:  34%|▎| 511/1495 [02:53<04:4
[Running Accuracy]: 0.7926,[Response]: C.<|endoftext|>, [Correct Ans]: Birthday cake, , [Prog]: 511:  34%|▎| 511/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the most eye-catching?\nA. Fork\nB. Cup\nC. Birthday cake\nD. Person\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focal point?
A. Light
B. Door
C. People
D. Wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focal point?
A. Light
B. Door
C. People
D. Wall
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focal point?\nA. Light\nB. Door\nC. People\nD. Wall\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7926,[Response]: C.<|endoftext|>, [Correct Ans]: Birthday cake, , [Prog]: 511:  34%|▎| 512/1495 
[Running Accuracy]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: People, , [Prog]: 512:  34%|▎| 512/1495 [02:54<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focal point?\nA. Light\nB. Door\nC. People\nD. Wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Noise
B. Low light
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Noise
B. Low light
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Noise\nB. Low light\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: People, , [Prog]: 512:  34%|▎| 513/1495 [02:54<
[Running Accuracy]: 0.7934,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 513:  34%|▎| 513/1495 [02:54<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Noise\nB. Low light\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the horse in the image vibrant?
A. Vibrant
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the horse in the image vibrant?
A. Vibrant
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the horse in the image vibrant?\nA. Vibrant\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7934,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 513:  34%|▎| 514/1495 [02:54<05
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 514:  34%|▎| 514/1495 [02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the horse in the image vibrant?\nA. Vibrant\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the red doll in the image?
A. Moderate
B. Blurry
C. Sharp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the red doll in the image?
A. Moderate
B. Blurry
C. Sharp
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the red doll in the image?\nA. Moderate\nB. Blurry\nC. Sharp\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 514:  34%|▎| 515/1495 [02
[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 515:  34%|▎| 515/1495 [02:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the red doll in the image?\nA. Moderate\nB. Blurry\nC. Sharp\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 515:  35%|▎| 516/1495 [02:5
[Running Accuracy]: 0.7907,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 516:  35%|▎| 516/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7907,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 516:  35%|▎| 517/1495 
[Running Accuracy]: 0.7892,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 517:  35%|▎| 517/1495 [02:55<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the most prominent in this image?
A. Antelope
B. Grass
C. Branch
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the most prominent in this image?
A. Antelope
B. Grass
C. Branch
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the most prominent in this image?\nA. Antelope\nB. Grass\nC. Branch\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7892,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 517:  35%|▎| 518/1495 [02:55<
[Running Accuracy]: 0.7896,[Response]: A.<|endoftext|>, [Correct Ans]: Antelope, , [Prog]: 518:  35%|▎| 518/1495 [02:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the most prominent in this image?\nA. Antelope\nB. Grass\nC. Branch\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the humans in this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the humans in this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the humans in this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7896,[Response]: A.<|endoftext|>, [Correct Ans]: Antelope, , [Prog]: 518:  35%|▎| 519/1495 [02:5
[Running Accuracy]: 0.7881,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 519:  35%|▎| 519/1495 [02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the humans in this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7881,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 519:  35%|▎| 520/1495 [02
[Running Accuracy]: 0.7865,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 520:  35%|▎| 520/1495 [02:56<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7865,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 520:  35%|▎| 521/1495 [02:56<04
[Running Accuracy]: 0.7850,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 521:  35%|▎| 521/1495 [02:56<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7850,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 521:  35%|▎| 522/1495 [02:57<
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 522:  35%|▎| 522/1495 [02:57<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 522:  35%|▎| 523/1495 [02:57<0
[Running Accuracy]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 523:  35%|▎| 523/1495 [02:57<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you describe the clarity of the desks?
A. Poor
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you describe the clarity of the desks?
A. Poor
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How would you describe the clarity of the desks?\nA. Poor\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 523:  35%|▎| 524/1495 [02:58<
[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 524:  35%|▎| 524/1495 [02:58<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you describe the clarity of the desks?\nA. Poor\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the center of this picture clearer than the surrounding areas?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the center of this picture clearer than the surrounding areas?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the center of this picture clearer than the surrounding areas?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 524:  35%|▎| 525/1495 [02:58<07
[Running Accuracy]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 525:  35%|▎| 525/1495 [02:58<07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the center of this picture clearer than the surrounding areas?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the purple flowers?
A. Low light
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the purple flowers?
A. Low light
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the purple flowers?\nA. Low light\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 525:  35%|▎| 526/1495 [02:59<08:
[Running Accuracy]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 526:  35%|▎| 526/1495 [02:59<08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the purple flowers?\nA. Low light\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most prominent color in the image?
A. White
B. Orange
C. Green
D. Purple
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most prominent color in the image?
A. White
B. Orange
C. Green
D. Purple
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. White\nB. Orange\nC. Green\nD. Purple\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 526:  35%|▎| 527/1495 [02:59<07
[Running Accuracy]: 0.7818,[Response]: B.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 527:  35%|▎| 527/1495 [02:59<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most prominent color in the image?\nA. White\nB. Orange\nC. Green\nD. Purple\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the red car in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the red car in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the red car in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7818,[Response]: B.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 527:  35%|▎| 528/1495 [03:00<
[Running Accuracy]: 0.7822,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 528:  35%|▎| 528/1495 [03:00<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the red car in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the image?
A. Too noisy
B. Too blurry
C. Too bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the image?
A. Too noisy
B. Too blurry
C. Too bright
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the image?\nA. Too noisy\nB. Too blurry\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7822,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 528:  35%|▎| 529/1495 [03:00<06
[Running Accuracy]: 0.7826,[Response]: C.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 529:  35%|▎| 529/1495 [03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the image?\nA. Too noisy\nB. Too blurry\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7826,[Response]: C.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 529:  35%|▎| 530/1495 [03
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 530:  35%|▎| 530/1495 [03:00<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 530:  36%|▎| 531/1495 [03:00<05:
[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 531:  36%|▎| 531/1495 [03:00<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image motion blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image motion blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 531:  36%|▎| 532/1495 [03:01<05:
[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 532:  36%|▎| 532/1495 [03:01<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 532:  36%|▎| 533/1495 [03:01<05:
[Running Accuracy]: 0.7842,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 533:  36%|▎| 533/1495 [03:01<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant color in the image?
A. The clothes of the woman on the right
B. The clothes of the woman on the left
C. The hair of the woman on the left
D. The hair of the woman on the right
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most vibrant color in the image?
A. The clothes of the woman on the right
B. The clothes of the woman on the left
C. The hair of the woman on the left
D. The hair of the woman on the right
Answer with the option's letter from the given choices directly.

prompts: [["What is the most vibrant color in the image?\nA. The clothes of the woman on the right\nB. The clothes of the woman on the left\nC. The hair of the woman on the left\nD. The hair of the woman on the right\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7842,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 533:  36%|▎| 534/1495 [03:01<05:
[Running Accuracy]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: The clothes of the woman on the left, , [Prog]:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant color in the image?\nA. The clothes of the woman on the right\nB. The clothes of the woman on the left\nC. The hair of the woman on the left\nD. The hair of the woman on the right\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion blurred?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image motion blurred?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image motion blurred?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: The clothes of the woman on the left, , [Prog]:
[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 535:  36%|▎| 535/1495 [03:02<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion blurred?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this dirty image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this dirty image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this dirty image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 535:  36%|▎| 536/1495 [03:02<04:
[Running Accuracy]: 0.7817,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 536:  36%|▎| 536/1495 [03:02<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this dirty image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the object in the image?
A. Very blurry
B. Moderately blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the object in the image?
A. Very blurry
B. Moderately blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the object in the image?\nA. Very blurry\nB. Moderately blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7817,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 536:  36%|▎| 537/1495 [03:02<
[Running Accuracy]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 537:  36%|▎| 537/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the object in the image?\nA. Very blurry\nB. Moderately blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the trash can in this image blurred?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the trash can in this image blurred?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the trash can in this image blurred?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 537:  36%|▎| 538/1495 [0
[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 538:  36%|▎| 538/1495 [03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the trash can in this image blurred?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject highlighted?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject highlighted?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject highlighted?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 538:  36%|▎| 539/1495 [03:0
[Running Accuracy]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 539:  36%|▎| 539/1495 [03:03<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject highlighted?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 539:  36%|▎| 540/1495 [03:03<04:
[Running Accuracy]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 540:  36%|▎| 540/1495 [03:03<04:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is/are the clearest object(s) in this picture?
A. Bottles
B. Window
C. Bucket
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is/are the clearest object(s) in this picture?
A. Bottles
B. Window
C. Bucket
Answer with the option's letter from the given choices directly.

prompts: [["What is/are the clearest object(s) in this picture?\nA. Bottles\nB. Window\nC. Bucket\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 540:  36%|▎| 541/1495 [03:03<04:3
[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Bottles, , [Prog]: 541:  36%|▎| 541/1495 [03:03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is/are the clearest object(s) in this picture?\nA. Bottles\nB. Window\nC. Bucket\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the people in this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the people in this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the people in this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Bottles, , [Prog]: 541:  36%|▎| 542/1495 [03:04
[Running Accuracy]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 542:  36%|▎| 542/1495 [03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the people in this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 542:  36%|▎| 543/1495 [03
[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 543:  36%|▎| 543/1495 [03:04<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe quality issue in the image?
A. Out of focus
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe quality issue in the image?
A. Out of focus
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe quality issue in the image?\nA. Out of focus\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 543:  36%|▎| 544/1495 [03:04<04:
[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 544:  36%|▎| 544/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe quality issue in the image?\nA. Out of focus\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the background in the image?
A. Blurry
B. Moderate
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the background in the image?
A. Blurry
B. Moderate
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the background in the image?\nA. Blurry\nB. Moderate\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 544:  36%|▎| 545/1495 [
[Running Accuracy]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 545:  36%|▎| 545/1495 [03:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the background in the image?\nA. Blurry\nB. Moderate\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction is the light in the image coming?
A. From the front
B. From the bottom
C. From the side
D. From the top
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction is the light in the image coming?
A. From the front
B. From the bottom
C. From the side
D. From the top
Answer with the option's letter from the given choices directly.

prompts: [["From which direction is the light in the image coming?\nA. From the front\nB. From the bottom\nC. From the side\nD. From the top\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 545:  37%|▎| 546/1495 [03:05<
[Running Accuracy]: 0.7784,[Response]: D.<|endoftext|>, [Correct Ans]: From the side, , [Prog]: 546:  37%|▎| 546/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction is the light in the image coming?\nA. From the front\nB. From the bottom\nC. From the side\nD. From the top\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7784,[Response]: D.<|endoftext|>, [Correct Ans]: From the side, , [Prog]: 546:  37%|▎| 547/1495 
[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 547:  37%|▎| 547/1495 [03:05<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the primary color tone of the image?
A. Blue
B. Red
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the primary color tone of the image?
A. Blue
B. Red
C. Green
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the primary color tone of the image?\nA. Blue\nB. Red\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 547:  37%|▎| 548/1495 [03:05<04:
[Running Accuracy]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 548:  37%|▎| 548/1495 [03:05<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the primary color tone of the image?\nA. Blue\nB. Red\nC. Green\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of the light in tis picture?
A. Underexposure
B. Noise
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion of the light in tis picture?
A. Underexposure
B. Noise
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion of the light in tis picture?\nA. Underexposure\nB. Noise\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 548:  37%|▎| 549/1495 [03:06<04
[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 549:  37%|▎| 549/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of the light in tis picture?\nA. Underexposure\nB. Noise\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flames in the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the flames in the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the flames in the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 549:  37%|▎| 550/1495 
[Running Accuracy]: 0.7782,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 550:  37%|▎| 550/1495 [03:06<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flames in the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image adopt the photography effect of black and white filter?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image adopt the photography effect of black and white filter?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image adopt the photography effect of black and white filter?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7782,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 550:  37%|▎| 551/1495 [03:06<04
[Running Accuracy]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 551:  37%|▎| 551/1495 [03:06<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image adopt the photography effect of black and white filter?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers in the image?
A. Low
B. High
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the flowers in the image?
A. Low
B. High
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the flowers in the image?\nA. Low\nB. High\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 551:  37%|▎| 552/1495 [03:07<04:
[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 552:  37%|▎| 552/1495 [03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers in the image?\nA. Low\nB. High\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is athlete No. 193 clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is athlete No. 193 clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is athlete No. 193 clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 552:  37%|▎| 553/1495 [03:0
[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 553:  37%|▎| 553/1495 [03:07<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is athlete No. 193 clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Colorful
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Colorful
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Colorful\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 553:  37%|▎| 554/1495 [03:07<05:
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 554:  37%|▎| 554/1495 [03:07<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Colorful\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 554:  37%|▎| 555/1495 [03:08<05
[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 555:  37%|▎| 555/1495 [03:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 555:  37%|▎| 556/1495 [03:08<
[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 556:  37%|▎| 556/1495 [03:08<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Between over-exposure and motion blur, which distortion occurs in this image?
A. None
B. Both
C. Only motion-blur
D. Only over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Between over-exposure and motion blur, which distortion occurs in this image?
A. None
B. Both
C. Only motion-blur
D. Only over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["Between over-exposure and motion blur, which distortion occurs in this image?\nA. None\nB. Both\nC. Only motion-blur\nD. Only over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 556:  37%|▎| 557/1495 [03:09<06:
[Running Accuracy]: 0.7738,[Response]: C.<|endoftext|>, [Correct Ans]: Both, , [Prog]: 557:  37%|▎| 557/1495 [03:09<06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Between over-exposure and motion blur, which distortion occurs in this image?\nA. None\nB. Both\nC. Only motion-blur\nD. Only over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there a lot of noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there a lot of noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there a lot of noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7738,[Response]: C.<|endoftext|>, [Correct Ans]: Both, , [Prog]: 557:  37%|▎| 558/1495 [03:09<06
[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 558:  37%|▎| 558/1495 [03:09<06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there a lot of noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image affected by noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image affected by noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image affected by noise?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 558:  37%|▎| 559/1495 [03:09<06:
[Running Accuracy]: 0.7710,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 559:  37%|▎| 559/1495 [03:09<06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image affected by noise?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the background in the image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the background in the image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the background in the image?\nA. Acceptable\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7710,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 559:  37%|▎| 560/1495 [03:10<05:5
[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 560:  37%|▎| 560/1495 [03:10<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the background in the image?\nA. Acceptable\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality problems does the image not have?
A. Overexposure
B. Underexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality problems does the image not have?
A. Overexposure
B. Underexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality problems does the image not have?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 560:  38%|▍| 561/1495 [03:10<05
[Running Accuracy]: 0.7701,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 561:  38%|▍| 561/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality problems does the image not have?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7701,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 561:  38%|▍| 562/1495 [0
[Running Accuracy]: 0.7705,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 562:  38%|▍| 562/1495 [03:10<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the people in this image look realistic, or computer-generated?
A. Computer-generated
B. Realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the people in this image look realistic, or computer-generated?
A. Computer-generated
B. Realistic
Answer with the option's letter from the given choices directly.

prompts: [["Do the people in this image look realistic, or computer-generated?\nA. Computer-generated\nB. Realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7705,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 562:  38%|▍| 563/1495 [03:11<05
[Running Accuracy]: 0.7709,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 563:  38%|▍| 563/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the people in this image look realistic, or computer-generated?\nA. Computer-generated\nB. Realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the coins very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the coins very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the coins very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 563:  38%|▍| 564/
[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 564:  38%|▍| 564/1495 [03:11<05:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the coins very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Please rate the color vividity of the parachute in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Please rate the color vividity of the parachute in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["Please rate the color vividity of the parachute in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 564:  38%|▍| 565/1495 [03:11<04:5
[Running Accuracy]: 0.7717,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 565:  38%|▍| 565/1495 [03:11<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Please rate the color vividity of the parachute in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry are the trees in the image?
A. Somewhat blurry
B. Not blurry at all
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry are the trees in the image?
A. Somewhat blurry
B. Not blurry at all
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry are the trees in the image?\nA. Somewhat blurry\nB. Not blurry at all\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7717,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 565:  38%|▍| 566/1495 [03:12<04
[Running Accuracy]: 0.7721,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 566:  38%|▍| 566/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry are the trees in the image?\nA. Somewhat blurry\nB. Not blurry at all\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is the most blurry?
A. Man's eyes
B. Man
C. Sticker on the wall
D. Man's clothes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the most blurry?
A. Man's eyes
B. Man
C. Sticker on the wall
D. Man's clothes
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the most blurry?\nA. Man's eyes\nB. Man\nC. Sticker on the wall\nD. Man's clothes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7721,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 566:  38%|▍| 567/1495 [0
[Running Accuracy]: 0.7707,[Response]: A.<|endoftext|>, [Correct Ans]: Sticker on the wall, , [Prog]: 567:  38%|▍| 567
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is the most blurry?\nA. Man's eyes\nB. Man\nC. Sticker on the wall\nD. Man's clothes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Blurriness
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Blurriness
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Blurriness\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7707,[Response]: A.<|endoftext|>, [Correct Ans]: Sticker on the wall, , [Prog]: 567:  38%|▍| 568
[Running Accuracy]: 0.7711,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 568:  38%|▍| 568/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Blurriness\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Underexposure
B. Brightness
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Underexposure
B. Brightness
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Underexposure\nB. Brightness\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7711,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 568:  38%|▍| 569/1495 [
[Running Accuracy]: 0.7715,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 569:  38%|▍| 569/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Underexposure\nB. Brightness\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the car main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the car main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the car main subject highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7715,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 569:  38%|▍| 570/1495 [0
[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 570:  38%|▍| 570/1495 [03:13<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the car main subject highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image blurry?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 570:  38%|▍| 571/1495 [03:14<06:
[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 571:  38%|▍| 571/1495 [03:14<06:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurry?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 571:  38%|▍| 572/1495 [03:14<05:5
[Running Accuracy]: 0.7710,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 572:  38%|▍| 572/1495 [03:14<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Noise
B. Under-exposure
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Noise
B. Under-exposure
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Noise\nB. Under-exposure\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7710,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 572:  38%|▍| 573/1495 [03:14<05:
[Running Accuracy]: 0.7714,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 573:  38%|▍| 573/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Noise\nB. Under-exposure\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7714,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 573:  38%|▍| 574/1495
[Running Accuracy]: 0.7718,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 574:  38%|▍| 574/1495 [03:15<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?
A. Out of focus
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality problems does not exist in this image?
A. Out of focus
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality problems does not exist in this image?\nA. Out of focus\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7718,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 574:  38%|▍| 575/1495 [03:15<04:
[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 575:  38%|▍| 575/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?\nA. Out of focus\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the little girl in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the little girl in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the little girl in the image?\nA. Clear\nB. Medium\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 575:  39%|▍| 576/1495 [
[Running Accuracy]: 0.7726,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 576:  39%|▍| 576/1495 [03:15<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the little girl in the image?\nA. Clear\nB. Medium\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe issue in the image?
A. Distortion
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe issue in the image?
A. Distortion
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe issue in the image?\nA. Distortion\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7726,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 576:  39%|▍| 577/1495 [03:16<
[Running Accuracy]: 0.7730,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 577:  39%|▍| 577/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe issue in the image?\nA. Distortion\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object has the brightest color in this image?
A. Yellow and purple alternating lights
B. Red and yellow alternating lights
C. Branches
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object has the brightest color in this image?
A. Yellow and purple alternating lights
B. Red and yellow alternating lights
C. Branches
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object has the brightest color in this image?\nA. Yellow and purple alternating lights\nB. Red and yellow alternating lights\nC. Branches\nD. Sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7730,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 577:  39%|▍| 578/1495 [
[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Red and yellow alternating lights, , [Prog]: 57
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object has the brightest color in this image?\nA. Yellow and purple alternating lights\nB. Red and yellow alternating lights\nC. Branches\nD. Sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Red and yellow alternating lights, , [Prog]: 57
[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 579:  39%|▍| 579/1495 [03:16<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the ocean ball in the image high?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the ocean ball in the image high?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the ocean ball in the image high?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 579:  39%|▍| 580/1495 [03:17<04:
[Running Accuracy]: 0.7724,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 580:  39%|▍| 580/1495 [03:17<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the ocean ball in the image high?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the texture of the grass very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the texture of the grass very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the texture of the grass very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7724,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 580:  39%|▍| 581/1495 [03:17<04
[Running Accuracy]: 0.7711,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 581:  39%|▍| 581/1495 [03:17<04:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the texture of the grass very clear in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image generally clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image generally clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image generally clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7711,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 581:  39%|▍| 582/1495 [03:17<05:5
[Running Accuracy]: 0.7715,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 582:  39%|▍| 582/1495 [03:17<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image generally clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the motorcycle in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the motorcycle in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the motorcycle in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7715,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 582:  39%|▍| 583/1495 [03:18<05:
[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 583:  39%|▍| 583/1495 [03:18<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the motorcycle in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 583:  39%|▍| 584/1495 [03:18<05
[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 584:  39%|▍| 584/1495 [03:18<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color of the castle in the image?
A. Monotonous
B. Moderate
C. Rich
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color of the castle in the image?
A. Monotonous
B. Moderate
C. Rich
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color of the castle in the image?\nA. Monotonous\nB. Moderate\nC. Rich\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 584:  39%|▍| 585/1495 [03:18<04
[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 585:  39%|▍| 585/1495 [03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color of the castle in the image?\nA. Monotonous\nB. Moderate\nC. Rich\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Clear
B. Blurry
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Blurry
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Blurry\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 585:  39%|▍| 586/1495 [03
[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 586:  39%|▍| 586/1495 [03:19<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Clear\nB. Blurry\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat the main subject of this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat the main subject of this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat the main subject of this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 586:  39%|▍| 587/1495 [03:19<0
[Running Accuracy]: 0.7717,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 587:  39%|▍| 587/1495 [03:19<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat the main subject of this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a vivid visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a vivid visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a vivid visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7717,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 587:  39%|▍| 588/1495 [03:19<04:
[Running Accuracy]: 0.7721,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 588:  39%|▍| 588/1495 [03:19<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a vivid visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7721,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 588:  39%|▍| 589/1495 [03:19<04:
[Running Accuracy]: 0.7708,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 589:  39%|▍| 589/1495 [03:19<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation in the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation in the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation in the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7708,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 589:  39%|▍| 590/1495 [03:20<04
[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 590:  39%|▍| 590/1495 [03:20<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation in the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the bird in the image?
A. Slightly blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the bird in the image?
A. Slightly blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the bird in the image?\nA. Slightly blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 590:  40%|▍| 591/1495 [03:20<04
[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 591:  40%|▍| 591/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the bird in the image?\nA. Slightly blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main object in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main object in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 591:  40%|▍| 592/149
[Running Accuracy]: 0.7720,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 592:  40%|▍| 592/1495 [03:20<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the poster on the wall in this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the poster on the wall in this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the poster on the wall in this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7720,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 592:  40%|▍| 593/1495 [03:21<05:
[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 593:  40%|▍| 593/1495 [03:21<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the poster on the wall in this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?
A. Warmful
B. Cheerful
C. Gloomy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the feeling of this image?
A. Warmful
B. Cheerful
C. Gloomy
Answer with the option's letter from the given choices directly.

prompts: [["How is the feeling of this image?\nA. Warmful\nB. Cheerful\nC. Gloomy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 593:  40%|▍| 594/1495 [03:21<05:
[Running Accuracy]: 0.7727,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 594:  40%|▍| 594/1495 [03:21<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?\nA. Warmful\nB. Cheerful\nC. Gloomy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7727,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 594:  40%|▍| 595/1495 [03:22<
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 595:  40%|▍| 595/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 595:  40%|▍| 596/1495 [
[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 596:  40%|▍| 596/1495 [03:22<05:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the cat in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the clearest in the image?
A. Grass slope
B. Brown horse
C. Wildflowers
D. White horse
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the clearest in the image?
A. Grass slope
B. Brown horse
C. Wildflowers
D. White horse
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the clearest in the image?\nA. Grass slope\nB. Brown horse\nC. Wildflowers\nD. White horse\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 596:  40%|▍| 597/1495 [03:22<05:0
[Running Accuracy]: 0.7739,[Response]: D.<|endoftext|>, [Correct Ans]: White horse, , [Prog]: 597:  40%|▍| 597/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the clearest in the image?\nA. Grass slope\nB. Brown horse\nC. Wildflowers\nD. White horse\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a bright visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a bright visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a bright visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7739,[Response]: D.<|endoftext|>, [Correct Ans]: White horse, , [Prog]: 597:  40%|▍| 598/1495 [0
[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 598:  40%|▍| 598/1495 [03:23<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a bright visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the circular fruit in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the circular fruit in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the circular fruit in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 598:  40%|▍| 599/1495 [03:23<04:
[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 599:  40%|▍| 599/1495 [03:23<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the circular fruit in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion in the image?
A. Compression artifacts
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion in the image?
A. Compression artifacts
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion in the image?\nA. Compression artifacts\nB. Overexposure\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 599:  40%|▍| 600/1495 [03:23<04:
[Running Accuracy]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 600:  40%|▍| 600/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion in the image?\nA. Compression artifacts\nB. Overexposure\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the main object of this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the main object of this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the main object of this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 600:  40%|▍| 601/1495 [
[Running Accuracy]: 0.7737,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 601:  40%|▍| 601/1495 [03:23<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the main object of this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion in this image?
A. Blur
B. Over-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion in this image?
A. Blur
B. Over-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion in this image?\nA. Blur\nB. Over-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7737,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 601:  40%|▍| 602/1495 [03:24<0
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 602:  40%|▍| 602/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion in this image?\nA. Blur\nB. Over-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Was the image taken with a shallow depth of field effect?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Was the image taken with a shallow depth of field effect?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Was the image taken with a shallow depth of field effect?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A. Yes

[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 602:  40%|▍| 603/1495 
[Running Accuracy]: 0.7745,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 603:  40%|▍| 603/1495 [03:24
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Was the image taken with a shallow depth of field effect?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A. Yes<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters in this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters in this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters in this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7745,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 603:  40%|▍| 604/1495 [03:25
[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 604:  40%|▍| 604/1495 [03:25<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters in this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion doesn't exist in this picture?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion doesn't exist in this picture?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion doesn't exist in this picture?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 604:  40%|▍| 605/1495 [03:25<
[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 605:  40%|▍| 605/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion doesn't exist in this picture?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting adequate for the spaceship in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting adequate for the spaceship in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting adequate for the spaceship in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 605:  41%|▍| 606/1495 
[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 606:  41%|▍| 606/1495 [03:26<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting adequate for the spaceship in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 606:  41%|▍| 607/1495 [03:26<06:
[Running Accuracy]: 0.7694,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 607:  41%|▍| 607/1495 [03:26<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which photography technique is not used in this image?
A. Background Bokeh
B. Motion Blur
C. Strong Contrast
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which photography technique is not used in this image?
A. Background Bokeh
B. Motion Blur
C. Strong Contrast
Answer with the option's letter from the given choices directly.

prompts: [["Which photography technique is not used in this image?\nA. Background Bokeh\nB. Motion Blur\nC. Strong Contrast\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7694,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 607:  41%|▍| 608/1495 [03:26<
[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 608:  41%|▍| 608/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which photography technique is not used in this image?\nA. Background Bokeh\nB. Motion Blur\nC. Strong Contrast\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the cat is clear in focus?
A. Its arm
B. Its back
C. Its ear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the cat is clear in focus?
A. Its arm
B. Its back
C. Its ear
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the cat is clear in focus?\nA. Its arm\nB. Its back\nC. Its ear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 608:  41%|▍| 609/1495 [0
[Running Accuracy]: 0.7701,[Response]: A.<|endoftext|>, [Correct Ans]: Its arm, , [Prog]: 609:  41%|▍| 609/1495 [03:27
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the cat is clear in focus?\nA. Its arm\nB. Its back\nC. Its ear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?
A. Overexposure
B. Out of focus
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is not a main distortion in this picture?
A. Overexposure
B. Out of focus
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is not a main distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7701,[Response]: A.<|endoftext|>, [Correct Ans]: Its arm, , [Prog]: 609:  41%|▍| 610/1495 [03:27
[Running Accuracy]: 0.7689,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 610:  41%|▍| 610/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall lighting condition in this image?
A. Radiant
B. Intermediate
C. Dim
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall lighting condition in this image?
A. Radiant
B. Intermediate
C. Dim
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall lighting condition in this image?\nA. Radiant\nB. Intermediate\nC. Dim\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7689,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 610:  41%|▍| 611/1495 [0
[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 611:  41%|▍| 611/1495 [03:27<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall lighting condition in this image?\nA. Radiant\nB. Intermediate\nC. Dim\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image highly saturated in color?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image highly saturated in color?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.

prompts: [["Is the image highly saturated in color?\nA. Low\nB. Moderate\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 611:  41%|▍| 612/1495 [03:28<04:
[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 612:  41%|▍| 612/1495 [03:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image highly saturated in color?\nA. Low\nB. Moderate\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the brightest part in this image?
A. ST
B. 56
C. 18
D. Capital letters E and S
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the brightest part in this image?
A. ST
B. 56
C. 18
D. Capital letters E and S
Answer with the option's letter from the given choices directly.

prompts: [["Which is the brightest part in this image?\nA. ST\nB. 56\nC. 18\nD. Capital letters E and S\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 612:  41%|▍| 613/1495 [03:2
[Running Accuracy]: 0.7667,[Response]: D.<|endoftext|>, [Correct Ans]: Capital letters E and S, , [Prog]: 613:  41%|▍|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the brightest part in this image?\nA. ST\nB. 56\nC. 18\nD. Capital letters E and S\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of flowers in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of flowers in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of flowers in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7667,[Response]: D.<|endoftext|>, [Correct Ans]: Capital letters E and S, , [Prog]: 613:  41%|▍|
[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 614:  41%|▍| 614/1495 [03:28<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of flowers in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 614:  41%|▍| 615/1495 [03:28<04
[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 615:  41%|▍| 615/1495 [03:28<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 615:  41%|▍| 616/1495 [03:29<
[Running Accuracy]: 0.7679,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 616:  41%|▍| 616/1495 [03:29<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters clear to see on the sign?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters clear to see on the sign?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters clear to see on the sign?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7679,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 616:  41%|▍| 617/1495 [03:29<05
[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 617:  41%|▍| 617/1495 [03:29<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters clear to see on the sign?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following red quality issues does this image not have?
A. Noise
B. Overexposure
C. Underexposure
D. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following red quality issues does this image not have?
A. Noise
B. Overexposure
C. Underexposure
D. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following red quality issues does this image not have?\nA. Noise\nB. Overexposure\nC. Underexposure\nD. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 617:  41%|▍| 618/1495 [03:30<05:
[Running Accuracy]: 0.7670,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 618:  41%|▍| 618/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following red quality issues does this image not have?\nA. Noise\nB. Overexposure\nC. Underexposure\nD. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which area in the image is especially brighter than other areas?
A. Top-left
B. Bottom-left
C. Bottom-right
D. Top-right
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which area in the image is especially brighter than other areas?
A. Top-left
B. Bottom-left
C. Bottom-right
D. Top-right
Answer with the option's letter from the given choices directly.

prompts: [["Which area in the image is especially brighter than other areas?\nA. Top-left\nB. Bottom-left\nC. Bottom-right\nD. Top-right\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7670,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 618:  41%|▍| 619/1495 [
[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Bottom-left, , [Prog]: 619:  41%|▍| 619/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which area in the image is especially brighter than other areas?\nA. Top-left\nB. Bottom-left\nC. Bottom-right\nD. Top-right\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is clear in focus in this image?
A. The ground
B. The desk
C. The lens
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is clear in focus in this image?
A. The ground
B. The desk
C. The lens
Answer with the option's letter from the given choices directly.

prompts: [["Which object is clear in focus in this image?\nA. The ground\nB. The desk\nC. The lens\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Bottom-left, , [Prog]: 619:  41%|▍| 620/1495 [0
[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: The lens, , [Prog]: 620:  41%|▍| 620/1495 [03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is clear in focus in this image?\nA. The ground\nB. The desk\nC. The lens\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the image high?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the image high?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the image high?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: The lens, , [Prog]: 620:  42%|▍| 621/1495 [03:3
[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 621:  42%|▍| 621/1495 [03:31<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the image high?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting sufficient and bright in the car part of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting sufficient and bright in the car part of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting sufficient and bright in the car part of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 621:  42%|▍| 622/1495 [03:31<04
[Running Accuracy]: 0.7669,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 622:  42%|▍| 622/1495 [03:31<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting sufficient and bright in the car part of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the brightest in this image?
A. White
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the brightest in this image?
A. White
B. Yellow
C. Green
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the brightest in this image?\nA. White\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7669,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 622:  42%|▍| 623/1495 [03:31<04:
[Running Accuracy]: 0.7673,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 623:  42%|▍| 623/1495 [03:31<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which color is the brightest in this image?\nA. White\nB. Yellow\nC. Green\nD. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bird emphasized in the center in the composition of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bird emphasized in the center in the composition of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bird emphasized in the center in the composition of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 623:  42%|▍| 624/1495 [03:31<04:
[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 624:  42%|▍| 624/1495 [03:31<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bird emphasized in the center in the composition of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?
A. Elderly person
B. Car
C. Man
D. House
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, which object is emphasized in the center?
A. Elderly person
B. Car
C. Man
D. House
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, which object is emphasized in the center?\nA. Elderly person\nB. Car\nC. Man\nD. House\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 624:  42%|▍| 625/1495 [03:32<04:
[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 625:  42%|▍| 625/1495 [03:32<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?\nA. Elderly person\nB. Car\nC. Man\nD. House\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the clarity of the glasses in the image of the person?
A. moderate
B. blurry
C. clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the clarity of the glasses in the image of the person?
A. moderate
B. blurry
C. clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the clarity of the glasses in the image of the person?\nA. moderate\nB. blurry\nC. clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 625:  42%|▍| 626/1495 [03:32<04:
[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: clear, , [Prog]: 626:  42%|▍| 626/1495 [03:32<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the clarity of the glasses in the image of the person?\nA. moderate\nB. blurry\nC. clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in the night sky?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise in the night sky?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise in the night sky?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: clear, , [Prog]: 626:  42%|▍| 627/1495 [03:33<0
[Running Accuracy]: 0.7687,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 627:  42%|▍| 627/1495 [03:33<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in the night sky?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the Christmas tree in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the Christmas tree in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the Christmas tree in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7687,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 627:  42%|▍| 628/1495 [03:33<05:
[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 628:  42%|▍| 628/1495 [03:33<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the Christmas tree in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 628:  42%|▍| 629/1495 [03:33<05
[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 629:  42%|▍| 629/1495 [03:33<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus in the image correct?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus in the image correct?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus in the image correct?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 629:  42%|▍| 630/1495 [03:34<05:
[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 630:  42%|▍| 630/1495 [03:34<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus in the image correct?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this image?
A. Bicycle
B. Ground
C. Sky
D. Grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of this image?
A. Bicycle
B. Ground
C. Sky
D. Grass
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. Bicycle\nB. Ground\nC. Sky\nD. Grass\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 630:  42%|▍| 631/1495 [03:34<05:
[Running Accuracy]: 0.7702,[Response]: A.<|endoftext|>, [Correct Ans]: Bicycle, , [Prog]: 631:  42%|▍| 631/1495 [03:34
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this image?\nA. Bicycle\nB. Ground\nC. Sky\nD. Grass\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the elderly person clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the elderly person clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the elderly person clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7702,[Response]: A.<|endoftext|>, [Correct Ans]: Bicycle, , [Prog]: 631:  42%|▍| 632/1495 [03:34
[Running Accuracy]: 0.7706,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 632:  42%|▍| 632/1495 [03:34<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the elderly person clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7706,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 632:  42%|▍| 633/1495 [03:35<04:
[Running Accuracy]: 0.7709,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 633:  42%|▍| 633/1495 [03:35<04:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 633:  42%|▍| 634/1495 [03:35<04:3
[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 634:  42%|▍| 634/1495 [03:35<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there noise in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image composed chaotic or organized?
A. Intermediate
B. Organized
C. Chaotic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image composed chaotic or organized?
A. Intermediate
B. Organized
C. Chaotic
Answer with the option's letter from the given choices directly.

prompts: [["Does the image composed chaotic or organized?\nA. Intermediate\nB. Organized\nC. Chaotic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 634:  42%|▍| 635/1495 [03:35<04:
[Running Accuracy]: 0.7717,[Response]: C.<|endoftext|>, [Correct Ans]: Chaotic, , [Prog]: 635:  42%|▍| 635/1495 [03:35
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image composed chaotic or organized?\nA. Intermediate\nB. Organized\nC. Chaotic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Motion blur
B. Overexposure
C. Underexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7717,[Response]: C.<|endoftext|>, [Correct Ans]: Chaotic, , [Prog]: 635:  43%|▍| 636/1495 [03:36
[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 636:  43%|▍| 636/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Acceptable\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 636:  43%|▍| 637/1495 [
[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 637:  43%|▍| 637/1495 [03:36<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?\nA. Acceptable\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 637:  43%|▍| 638/1495 [03:36<04
[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 638:  43%|▍| 638/1495 [03:36<04:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focus in this image?
A. Woman riding a bike
B. Building
C. Pine tree
D. Man in black clothing walking
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. Woman riding a bike
B. Building
C. Pine tree
D. Man in black clothing walking
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. Woman riding a bike\nB. Building\nC. Pine tree\nD. Man in black clothing walking\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 638:  43%|▍| 639/1495 [03:37<04:3
[Running Accuracy]: 0.7731,[Response]: A.<|endoftext|>, [Correct Ans]: Woman riding a bike, , [Prog]: 639:  43%|▍| 639
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focus in this image?\nA. Woman riding a bike\nB. Building\nC. Pine tree\nD. Man in black clothing walking\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the trees in the image?
A. Green
B. Purple
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the trees in the image?
A. Green
B. Purple
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the trees in the image?\nA. Green\nB. Purple\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: A.<|endoftext|>, [Correct Ans]: Woman riding a bike, , [Prog]: 639:  43%|▍| 640
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 640:  43%|▍| 640/1495 [03:37<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the trees in the image?\nA. Green\nB. Purple\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Underexposure
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Underexposure
B. Noise
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Underexposure\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 640:  43%|▍| 641/1495 [03:37<0
[Running Accuracy]: 0.7738,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 641:  43%|▍| 641/1495 [03:37<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Underexposure\nB. Noise\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any details of background in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any details of background in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any details of background in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7738,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 641:  43%|▍| 642/1495 [03:37<04
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 642:  43%|▍| 642/1495 [03:37<04:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any details of background in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is overall lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is overall lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is overall lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 642:  43%|▍| 643/1495 [03:38<05:3
[Running Accuracy]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 643:  43%|▍| 643/1495 [03:38<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is overall lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is this picture?
A. Moderate
B. Mild
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How noisy is this picture?
A. Moderate
B. Mild
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How noisy is this picture?\nA. Moderate\nB. Mild\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 643:  43%|▍| 644/1495 [03:38<
[Running Accuracy]: 0.7748,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 644:  43%|▍| 644/1495 [03:38<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is this picture?\nA. Moderate\nB. Mild\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the face of the small figurines look clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the face of the small figurines look clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the face of the small figurines look clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7748,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 644:  43%|▍| 645/1495 [03:39<
[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 645:  43%|▍| 645/1495 [03:39<04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the face of the small figurines look clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the animal in this image?
A. Noise
B. Under-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the animal in this image?
A. Noise
B. Under-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the animal in this image?\nA. Noise\nB. Under-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 645:  43%|▍| 646/1495 [03:39<04:3
[Running Accuracy]: 0.7755,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 646:  43%|▍| 646/1495 [03:39<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the animal in this image?\nA. Noise\nB. Under-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the subject in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the subject in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7755,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 646:  43%|▍| 647/1495 [03:39<04
[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 647:  43%|▍| 647/1495 [03:39<04:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the subject in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?
A. Green
B. Blue
C. Red
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone in the image?
A. Green
B. Blue
C. Red
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone in the image?\nA. Green\nB. Blue\nC. Red\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 647:  43%|▍| 648/1495 [03:39<04:1
[Running Accuracy]: 0.7747,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 648:  43%|▍| 648/1495 [03:39<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?\nA. Green\nB. Blue\nC. Red\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7747,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 648:  43%|▍| 649/1495 [03:40<04
[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 649:  43%|▍| 649/1495 [03:40<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the fireworks the focus in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the fireworks the focus in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the fireworks the focus in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 649:  43%|▍| 650/1495 [03:40<04
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 650:  43%|▍| 650/1495 [03:40<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the fireworks the focus in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in the image?
A. Compression distortion
B. Overexposure
C. Motion blur
D. No issues
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issues exist in the image?
A. Compression distortion
B. Overexposure
C. Motion blur
D. No issues
Answer with the option's letter from the given choices directly.

prompts: [["What quality issues exist in the image?\nA. Compression distortion\nB. Overexposure\nC. Motion blur\nD. No issues\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 650:  44%|▍| 651/1495 [03:40<04:
[Running Accuracy]: 0.7742,[Response]: D.<|endoftext|>, [Correct Ans]: No issues, , [Prog]: 651:  44%|▍| 651/1495 [03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in the image?\nA. Compression distortion\nB. Overexposure\nC. Motion blur\nD. No issues\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the wolf very clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the wolf very clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the wolf very clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7742,[Response]: D.<|endoftext|>, [Correct Ans]: No issues, , [Prog]: 651:  44%|▍| 652/1495 [03:
[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 652:  44%|▍| 652/1495 [03:41<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the wolf very clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?
A. Noise
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does this image not have?
A. Noise
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does this image not have?\nA. Noise\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 652:  44%|▍| 653/1495 [03:41<04:
[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 653:  44%|▍| 653/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?\nA. Noise\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the composition in this image?
A. Potted plant
B. Desk lamp
C. Desk
D. Window
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the composition in this image?
A. Potted plant
B. Desk lamp
C. Desk
D. Window
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the composition in this image?\nA. Potted plant\nB. Desk lamp\nC. Desk\nD. Window\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 653:  44%|▍| 654/1495 [
[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Desk, , [Prog]: 654:  44%|▍| 654/1495 [03:41<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the composition in this image?\nA. Potted plant\nB. Desk lamp\nC. Desk\nD. Window\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the focus?
A. Woman
B. Plant
C. House
D. Man with a hat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. Woman
B. Plant
C. House
D. Man with a hat
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. Woman\nB. Plant\nC. House\nD. Man with a hat\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7722,[Response]: C.<|endoftext|>, [Correct Ans]: Desk, , [Prog]: 654:  44%|▍| 655/1495 [03:42<04
[Running Accuracy]: 0.7725,[Response]: D.<|endoftext|>, [Correct Ans]: Man with a hat, , [Prog]: 655:  44%|▍| 655/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the focus?\nA. Woman\nB. Plant\nC. House\nD. Man with a hat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the cartoon statue in the middle of the image?
A. Noise
B. Colorless
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the cartoon statue in the middle of the image?
A. Noise
B. Colorless
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the cartoon statue in the middle of the image?\nA. Noise\nB. Colorless\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7725,[Response]: D.<|endoftext|>, [Correct Ans]: Man with a hat, , [Prog]: 655:  44%|▍| 656/1495
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 656:  44%|▍| 656/1495 [03:42<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the cartoon statue in the middle of the image?\nA. Noise\nB. Colorless\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the motion blur in this image?
A. No motion blur
B. Weak motion blur
C. Moderate motion blur
D. Severe motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the motion blur in this image?
A. No motion blur
B. Weak motion blur
C. Moderate motion blur
D. Severe motion blur
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the motion blur in this image?\nA. No motion blur\nB. Weak motion blur\nC. Moderate motion blur\nD. Severe motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 656:  44%|▍| 657/1495 [03:43<06
[Running Accuracy]: 0.7732,[Response]: D.<|endoftext|>, [Correct Ans]: Severe motion blur, , [Prog]: 657:  44%|▍| 657/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the motion blur in this image?\nA. No motion blur\nB. Weak motion blur\nC. Moderate motion blur\nD. Severe motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear and sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear and sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7732,[Response]: D.<|endoftext|>, [Correct Ans]: Severe motion blur, , [Prog]: 657:  44%|▍| 658/
[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 658:  44%|▍| 658/1495 [03:43<05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the texture details of the flowers visible?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the texture details of the flowers visible?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the texture details of the flowers visible?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 658:  44%|▍| 659/1495 [03:43<05:2
[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 659:  44%|▍| 659/1495 [03:43<05:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the texture details of the flowers visible?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?
A. Car
B. Ground
C. Building
D. Plant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focal point in this image?
A. Car
B. Ground
C. Building
D. Plant
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focal point in this image?\nA. Car\nB. Ground\nC. Building\nD. Plant\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 659:  44%|▍| 660/1495 [03:44<04:5
[Running Accuracy]: 0.7742,[Response]: A.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 660:  44%|▍| 660/1495 [03:44<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?\nA. Car\nB. Ground\nC. Building\nD. Plant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. The boy wearing a black top
B. The girl wearing a black top
C. The girl wearing a red top
D. The girl wearing a white top
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. The boy wearing a black top
B. The girl wearing a black top
C. The girl wearing a red top
D. The girl wearing a white top
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. The boy wearing a black top\nB. The girl wearing a black top\nC. The girl wearing a red top\nD. The girl wearing a white top\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7742,[Response]: A.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 660:  44%|▍| 661/1495 [03:44<04:
[Running Accuracy]: 0.7731,[Response]: C.<|endoftext|>, [Correct Ans]: The girl wearing a black top, , [Prog]: 661:  4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. The boy wearing a black top\nB. The girl wearing a black top\nC. The girl wearing a red top\nD. The girl wearing a white top\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the color saturation of the red bus in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the color saturation of the red bus in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How's the color saturation of the red bus in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: C.<|endoftext|>, [Correct Ans]: The girl wearing a black top, , [Prog]: 661:  4
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 662:  44%|▍| 662/1495 [03:44<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the color saturation of the red bus in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 662:  44%|▍| 663/1495 [03:45<04
[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 663:  44%|▍| 663/1495 [03:45<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 663:  44%|▍| 664/1495 [03:45<
[Running Accuracy]: 0.7726,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 664:  44%|▍| 664/1495 [03:45<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems does the image have?
A. Motion blur
B. Noise
C. Excessive color aberration
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems does the image have?
A. Motion blur
B. Noise
C. Excessive color aberration
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems does the image have?\nA. Motion blur\nB. Noise\nC. Excessive color aberration\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7726,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 664:  44%|▍| 665/1495 [03:45<04:
[Running Accuracy]: 0.7714,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 665:  44%|▍| 665/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems does the image have?\nA. Motion blur\nB. Noise\nC. Excessive color aberration\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of this image?
A. Too dark
B. Just fine
C. Too bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of this image?
A. Too dark
B. Just fine
C. Too bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of this image?\nA. Too dark\nB. Just fine\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7714,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 665:  45%|▍| 666/1495 [
[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 666:  45%|▍| 666/1495 [03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of this image?\nA. Too dark\nB. Just fine\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness is present in the buildings in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blurriness is present in the buildings in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blurriness is present in the buildings in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 666:  45%|▍| 667/1495 [03:
[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 667:  45%|▍| 667/1495 [03:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness is present in the buildings in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 667:  45%|▍| 668/1495 [03:4
[Running Accuracy]: 0.7710,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 668:  45%|▍| 668/1495 [03:46<04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the ground rich in texture in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the ground rich in texture in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the ground rich in texture in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7710,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 668:  45%|▍| 669/1495 [03:46<04:1
[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 669:  45%|▍| 669/1495 [03:46<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the ground rich in texture in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vase and flowers emphasized in the center in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vase and flowers emphasized in the center in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the vase and flowers emphasized in the center in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 669:  45%|▍| 670/1495 [03:47<04:
[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 670:  45%|▍| 670/1495 [03:47<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vase and flowers emphasized in the center in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the vehicle in the picture?
A. Not blurry at all
B. Moderately blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the vehicle in the picture?
A. Not blurry at all
B. Moderately blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the vehicle in the picture?\nA. Not blurry at all\nB. Moderately blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7716,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 670:  45%|▍| 671/1495 [03:47<04:
[Running Accuracy]: 0.7720,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 671:  45%|▍| 671/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the vehicle in the picture?\nA. Not blurry at all\nB. Moderately blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color saturation high?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color saturation high?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color saturation high?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7720,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 671:  45%|▍| 672/1495 [0
[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 672:  45%|▍| 672/1495 [03:47<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color saturation high?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the men and women holding drinks clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the men and women holding drinks clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the men and women holding drinks clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7723,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 672:  45%|▍| 673/1495 [03:48<04
[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 673:  45%|▍| 673/1495 [03:48<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the men and women holding drinks clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the starfish necklace emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the starfish necklace emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the starfish necklace emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 673:  45%|▍| 674/1495 [03:48<04:1
[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 674:  45%|▍| 674/1495 [03:48<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the starfish necklace emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 674:  45%|▍| 675/1495 [03:48<04:
[Running Accuracy]: 0.7733,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 675:  45%|▍| 675/1495 [03:48<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7733,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 675:  45%|▍| 676/1495 [03:49<04:
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 676:  45%|▍| 676/1495 [03:49<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the vegetation in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the vegetation in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the vegetation in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 676:  45%|▍| 677/1495 [03:49<04:0
[Running Accuracy]: 0.7740,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 677:  45%|▍| 677/1495 [03:49<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the vegetation in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7740,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 677:  45%|▍| 678/1495 [03:49<03
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 678:  45%|▍| 678/1495 [03:49
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there underexposure in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there underexposure in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there underexposure in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 678:  45%|▍| 679/1495 [03:49
[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 679:  45%|▍| 679/1495 [03:49<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there underexposure in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the leaves in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the leaves in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the leaves in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 679:  45%|▍| 680/1495 [03:50<03:5
[Running Accuracy]: 0.7721,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 680:  45%|▍| 680/1495 [03:50<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the leaves in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7721,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 680:  46%|▍| 681/1495 [03:50<04:3
[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 681:  46%|▍| 681/1495 [03:50<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the duck doll in the image?
A. High saturation
B. Low saturation
C. Moderate saturation
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the duck doll in the image?
A. High saturation
B. Low saturation
C. Moderate saturation
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the duck doll in the image?\nA. High saturation\nB. Low saturation\nC. Moderate saturation\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 681:  46%|▍| 682/1495 [03:50<04:
[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: High saturation, , [Prog]: 682:  46%|▍| 682/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the duck doll in the image?\nA. High saturation\nB. Low saturation\nC. Moderate saturation\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the picture?
A. Good
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is the picture?
A. Good
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the picture?\nA. Good\nB. Dark\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: High saturation, , [Prog]: 682:  46%|▍| 683/149
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 683:  46%|▍| 683/1495 [03:51<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the picture?\nA. Good\nB. Dark\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues exist in the image?
A. Overexposure
B. Motion blur
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality issues exist in the image?
A. Overexposure
B. Motion blur
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality issues exist in the image?\nA. Overexposure\nB. Motion blur\nC. Distortion\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 683:  46%|▍| 684/1495 [03:51<04
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 684:  46%|▍| 684/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality issues exist in the image?\nA. Overexposure\nB. Motion blur\nC. Distortion\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 684:  46%|▍| 685/1495 [
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 685:  46%|▍| 685/1495 [03:51<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the artifact level in this image?
A. Medium
B. Weak
C. Strong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the artifact level in this image?
A. Medium
B. Weak
C. Strong
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the artifact level in this image?\nA. Medium\nB. Weak\nC. Strong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 685:  46%|▍| 686/1495 [03:52<04:
[Running Accuracy]: 0.7741,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 686:  46%|▍| 686/1495 [03:52<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the artifact level in this image?\nA. Medium\nB. Weak\nC. Strong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7741,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 686:  46%|▍| 687/1495 [03:52<
[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 687:  46%|▍| 687/1495 [03:52<04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the characters in the image?
A. Gray
B. Red
C. Blue
D. Green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the characters in the image?
A. Gray
B. Red
C. Blue
D. Green
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the characters in the image?\nA. Gray\nB. Red\nC. Blue\nD. Green\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 687:  46%|▍| 688/1495 [03:52<04:0
[Running Accuracy]: 0.7747,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 688:  46%|▍| 688/1495 [03:52<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the characters in the image?\nA. Gray\nB. Red\nC. Blue\nD. Green\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image weird?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image weird?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image weird?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7747,[Response]: D.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 688:  46%|▍| 689/1495 [03:53<0
[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 689:  46%|▍| 689/1495 [03:53<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image weird?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 689:  46%|▍| 690/1495 [03:53<04:
[Running Accuracy]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 690:  46%|▍| 690/1495 [03:53<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is the focal point?
A. Blanket
B. Kitten
C. Clothes
D. Hand
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the focal point?
A. Blanket
B. Kitten
C. Clothes
D. Hand
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the focal point?\nA. Blanket\nB. Kitten\nC. Clothes\nD. Hand\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 690:  46%|▍| 691/1495 [03:53<04:
[Running Accuracy]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 691:  46%|▍| 691/1495 [03:53<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is the focal point?\nA. Blanket\nB. Kitten\nC. Clothes\nD. Hand\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the texture of the leaves clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the texture of the leaves clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the texture of the leaves clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 691:  46%|▍| 692/1495 [03:54<
[Running Accuracy]: 0.7760,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 692:  46%|▍| 692/1495 [03:54<04:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the texture of the leaves clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this image?
A. Horse
B. Person
C. Green plants
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of this image?
A. Horse
B. Person
C. Green plants
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. Horse\nB. Person\nC. Green plants\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7760,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 692:  46%|▍| 693/1495 [03:54<04:3
[Running Accuracy]: 0.7763,[Response]: A.<|endoftext|>, [Correct Ans]: Horse, , [Prog]: 693:  46%|▍| 693/1495 [03:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this image?\nA. Horse\nB. Person\nC. Green plants\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the focus?
A. Large Surface
B. Table
C. Shoes
D. Brochure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the focus?
A. Large Surface
B. Table
C. Shoes
D. Brochure
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the focus?\nA. Large Surface\nB. Table\nC. Shoes\nD. Brochure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7763,[Response]: A.<|endoftext|>, [Correct Ans]: Horse, , [Prog]: 693:  46%|▍| 694/1495 [03:54<0
[Running Accuracy]: 0.7767,[Response]: D.<|endoftext|>, [Correct Ans]: Brochure, , [Prog]: 694:  46%|▍| 694/1495 [03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image is the focus?\nA. Large Surface\nB. Table\nC. Shoes\nD. Brochure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7767,[Response]: D.<|endoftext|>, [Correct Ans]: Brochure, , [Prog]: 694:  46%|▍| 695/1495 [03:5
[Running Accuracy]: 0.7755,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 695:  46%|▍| 695/1495 [03:55<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?
A. Happy
B. Fresh
C. Bright
D. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual impression does the image give?
A. Happy
B. Fresh
C. Bright
D. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does the image give?\nA. Happy\nB. Fresh\nC. Bright\nD. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7755,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 695:  47%|▍| 696/1495 [03:55<04:
[Running Accuracy]: 0.7759,[Response]: D.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 696:  47%|▍| 696/1495 [03:55<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?\nA. Happy\nB. Fresh\nC. Bright\nD. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background in the image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background in the image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background in the image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7759,[Response]: D.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 696:  47%|▍| 697/1495 [03:55<04
[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 697:  47%|▍| 697/1495 [03:55<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background in the image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Underexposure
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Underexposure
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Underexposure\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 697:  47%|▍| 698/1495 [03:56<
[Running Accuracy]: 0.7751,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 698:  47%|▍| 698/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Underexposure\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the textures of the cat clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the textures of the cat clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the textures of the cat clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7751,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 698:  47%|▍| 699/1495 [
[Running Accuracy]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 699:  47%|▍| 699/1495 [03:56<05:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the textures of the cat clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is severely affected by motion blur?
A. Cloud
B. Railing
C. Sky
D. Person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is severely affected by motion blur?
A. Cloud
B. Railing
C. Sky
D. Person
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is severely affected by motion blur?\nA. Cloud\nB. Railing\nC. Sky\nD. Person\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 699:  47%|▍| 700/1495 [03:57<05:1
[Running Accuracy]: 0.7757,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 700:  47%|▍| 700/1495 [03:57<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image is severely affected by motion blur?\nA. Cloud\nB. Railing\nC. Sky\nD. Person\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sky of this image overexposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky of this image overexposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky of this image overexposed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7757,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 700:  47%|▍| 701/1495 [03:57<
[Running Accuracy]: 0.7760,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 701:  47%|▍| 701/1495 [03:57<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sky of this image overexposed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7760,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 701:  47%|▍| 702/1495 [03:57<04:
[Running Accuracy]: 0.7764,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 702:  47%|▍| 702/1495 [03:57<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7764,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 702:  47%|▍| 703/1495 [03:58<04:
[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 703:  47%|▍| 703/1495 [03:58<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 703:  47%|▍| 704/1495 [03:58<
[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 704:  47%|▍| 704/1495 [03:58<04:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 704:  47%|▍| 705/1495 [03:58<04:1
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 705:  47%|▍| 705/1495 [03:58<04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 705:  47%|▍| 706/1495 [03:59<05:3
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 706:  47%|▍| 706/1495 [03:59<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the predominant distortion in this image?
A. Overexposure
B. Compression Artifacts
C. Blur
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the predominant distortion in this image?
A. Overexposure
B. Compression Artifacts
C. Blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the predominant distortion in this image?\nA. Overexposure\nB. Compression Artifacts\nC. Blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 706:  47%|▍| 707/1495 [03:59<04:
[Running Accuracy]: 0.7765,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 707:  47%|▍| 707/1495 [03:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the predominant distortion in this image?\nA. Overexposure\nB. Compression Artifacts\nC. Blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7765,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 707:  47%|▍| 708/1495 [03:59<0
[Running Accuracy]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 708:  47%|▍| 708/1495 [03:59<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 708:  47%|▍| 709/1495 [04:00<04:
[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 709:  47%|▍| 709/1495 [04:00<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Normal\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 709:  47%|▍| 710/1495 [04:00<04
[Running Accuracy]: 0.7775,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 710:  47%|▍| 710/1495 [04:00<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?
A. Gloomy
B. Disgusting
C. Excited
D. Cheerful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the feeling of this image?
A. Gloomy
B. Disgusting
C. Excited
D. Cheerful
Answer with the option's letter from the given choices directly.

prompts: [["How is the feeling of this image?\nA. Gloomy\nB. Disgusting\nC. Excited\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7775,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 710:  48%|▍| 711/1495 [04:00<04
[Running Accuracy]: 0.7778,[Response]: D.<|endoftext|>, [Correct Ans]: Cheerful, , [Prog]: 711:  48%|▍| 711/1495 [04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the feeling of this image?\nA. Gloomy\nB. Disgusting\nC. Excited\nD. Cheerful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the desk in this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the desk in this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the desk in this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7778,[Response]: D.<|endoftext|>, [Correct Ans]: Cheerful, , [Prog]: 711:  48%|▍| 712/1495 [04:0
[Running Accuracy]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 712:  48%|▍| 712/1495 [04:01<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the desk in this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a bright visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a bright visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a bright visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 712:  48%|▍| 713/1495 [04:01<04
[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 713:  48%|▍| 713/1495 [04:01<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a bright visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 713:  48%|▍| 714/1495 [04:01<04:
[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 714:  48%|▍| 714/1495 [04:01<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the characters in the image rich?
A. Not rich
B. Rich
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the characters in the image rich?
A. Not rich
B. Rich
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the characters in the image rich?\nA. Not rich\nB. Rich\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 714:  48%|▍| 715/1495 [04:02<04:
[Running Accuracy]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: Not rich, , [Prog]: 715:  48%|▍| 715/1495 [04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the characters in the image rich?\nA. Not rich\nB. Rich\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the main lighting source of this image?
A. Sunlight
B. Reflection
C. Lightbulb
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the main lighting source of this image?
A. Sunlight
B. Reflection
C. Lightbulb
Answer with the option's letter from the given choices directly.

prompts: [["Which is the main lighting source of this image?\nA. Sunlight\nB. Reflection\nC. Lightbulb\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: Not rich, , [Prog]: 715:  48%|▍| 716/1495 [04:0
[Running Accuracy]: 0.7765,[Response]: A.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 716:  48%|▍| 716/1495 [04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the main lighting source of this image?\nA. Sunlight\nB. Reflection\nC. Lightbulb\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the focus?
A. Large tree
B. House
C. Two puppies
D. Grassland
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. Large tree
B. House
C. Two puppies
D. Grassland
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. Large tree\nB. House\nC. Two puppies\nD. Grassland\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7765,[Response]: A.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 716:  48%|▍| 717/1495 [04:0
[Running Accuracy]: 0.7768,[Response]: C.<|endoftext|>, [Correct Ans]: Two puppies, , [Prog]: 717:  48%|▍| 717/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in this image is the focus?\nA. Large tree\nB. House\nC. Two puppies\nD. Grassland\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7768,[Response]: C.<|endoftext|>, [Correct Ans]: Two puppies, , [Prog]: 717:  48%|▍| 718/1495 [0
[Running Accuracy]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 718:  48%|▍| 718/1495 [04:03<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the plants on the right side of the image brighter than the plants on the left side?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the plants on the right side of the image brighter than the plants on the left side?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the plants on the right side of the image brighter than the plants on the left side?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 718:  48%|▍| 719/1495 [04:04<04
[Running Accuracy]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 719:  48%|▍| 719/1495 [04:04<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the plants on the right side of the image brighter than the plants on the left side?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most serious problem in the image?
A. Motion blur
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most serious problem in the image?
A. Motion blur
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most serious problem in the image?\nA. Motion blur\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 719:  48%|▍| 720/1495 [04:04<04:
[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 720:  48%|▍| 720/1495 [04:04<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most serious problem in the image?\nA. Motion blur\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 720:  48%|▍| 721/1495 [04:04<0
[Running Accuracy]: 0.7781,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 721:  48%|▍| 721/1495 [04:04<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Dos the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Dos the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Dos the ground contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7781,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 721:  48%|▍| 722/1495 [04:05<04:
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 722:  48%|▍| 722/1495 [04:05<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Dos the ground contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What are the lighting conditions for the main characters in the image?
A. Medium
B. Bright
C. Dim
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are the lighting conditions for the main characters in the image?
A. Medium
B. Bright
C. Dim
Answer with the option's letter from the given choices directly.

prompts: [["What are the lighting conditions for the main characters in the image?\nA. Medium\nB. Bright\nC. Dim\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 722:  48%|▍| 723/1495 [04:05<04:
[Running Accuracy]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 723:  48%|▍| 723/1495 [04:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What are the lighting conditions for the main characters in the image?\nA. Medium\nB. Bright\nC. Dim\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Medium
B. Very low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Medium
B. Very low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Medium\nB. Very low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 723:  48%|▍| 724/1495 [04:05<
[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Very low, , [Prog]: 724:  48%|▍| 724/1495 [04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Medium\nB. Very low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise on the wall in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise on the wall in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Very low, , [Prog]: 724:  48%|▍| 725/1495 [04:0
[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 725:  48%|▍| 725/1495 [04:05<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise on the wall in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the trees in this image look noisy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the trees in this image look noisy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the trees in this image look noisy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 725:  49%|▍| 726/1495 [04:06<04:
[Running Accuracy]: 0.7782,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 726:  49%|▍| 726/1495 [04:06<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the trees in this image look noisy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background of the image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background of the image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background of the image?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7782,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 726:  49%|▍| 727/1495 [04:06<03:
[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 727:  49%|▍| 727/1495 [04:06<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background of the image?\nA. Moderate\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vehicle in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 727:  49%|▍| 728/1495 [04:06<
[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 728:  49%|▍| 728/1495 [04:06<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the blue-shirt man is motion blurred?
A. Body
B. Head
C. Hand
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the blue-shirt man is motion blurred?
A. Body
B. Head
C. Hand
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the blue-shirt man is motion blurred?\nA. Body\nB. Head\nC. Hand\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 728:  49%|▍| 729/1495 [04:07<04:0
[Running Accuracy]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Hand, , [Prog]: 729:  49%|▍| 729/1495 [04:07<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the blue-shirt man is motion blurred?\nA. Body\nB. Head\nC. Hand\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Hand, , [Prog]: 729:  49%|▍| 730/1495 [04:07<04
[Running Accuracy]: 0.7795,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 730:  49%|▍| 730/1495 [04:07<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the eyes of the dog in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the eyes of the dog in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the eyes of the dog in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7795,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 730:  49%|▍| 731/1495 [04:07<03
[Running Accuracy]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 731:  49%|▍| 731/1495 [04:07<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the eyes of the dog in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of this image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of this image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of this image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 731:  49%|▍| 732/1495 [04:08<04:0
[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 732:  49%|▍| 732/1495 [04:08<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of this image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the quality of this image acceptable?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the quality of this image acceptable?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the quality of this image acceptable?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 732:  49%|▍| 733/1495 [04:08<05:
[Running Accuracy]: 0.7804,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 733:  49%|▍| 733/1495 [04:08<05:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the quality of this image acceptable?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the image sharpness?
A. Clear
B. Blurry
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the image sharpness?
A. Clear
B. Blurry
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What is the image sharpness?\nA. Clear\nB. Blurry\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7804,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 733:  49%|▍| 734/1495 [04:09<04:3
[Running Accuracy]: 0.7793,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 734:  49%|▍| 734/1495 [04:09<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the image sharpness?\nA. Clear\nB. Blurry\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7793,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 734:  49%|▍| 735/1495 [04:09<
[Running Accuracy]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 735:  49%|▍| 735/1495 [04:09<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is this image?
A. Moderately noisy
B. Not noisy
C. Very noisy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How noisy is this image?
A. Moderately noisy
B. Not noisy
C. Very noisy
Answer with the option's letter from the given choices directly.

prompts: [["How noisy is this image?\nA. Moderately noisy\nB. Not noisy\nC. Very noisy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 735:  49%|▍| 736/1495 [04:09<05
[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Not noisy, , [Prog]: 736:  49%|▍| 736/1495 [04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is this image?\nA. Moderately noisy\nB. Not noisy\nC. Very noisy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an underexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Not noisy, , [Prog]: 736:  49%|▍| 737/1495 [04:
[Running Accuracy]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 737:  49%|▍| 737/1495 [04:10<04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the posters in this image?
A. Noise
B. Low contrast
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the posters in this image?
A. Noise
B. Low contrast
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the posters in this image?\nA. Noise\nB. Low contrast\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 737:  49%|▍| 738/1495 [04:10<05:3
[Running Accuracy]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 738:  49%|▍| 738/1495 [04:10<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the posters in this image?\nA. Noise\nB. Low contrast\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two people in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two people in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the two people in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 738:  49%|▍| 739/1495 [04:11<05
[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 739:  49%|▍| 739/1495 [04:11<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two people in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main light source in the image?
A. Sunlight
B. Streetlight
C. Reflected light
D. Moonlight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main light source in the image?
A. Sunlight
B. Streetlight
C. Reflected light
D. Moonlight
Answer with the option's letter from the given choices directly.

prompts: [["What is the main light source in the image?\nA. Sunlight\nB. Streetlight\nC. Reflected light\nD. Moonlight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 739:  49%|▍| 740/1495 [04:11<04:
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 740:  49%|▍| 740/1495 [04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main light source in the image?\nA. Sunlight\nB. Streetlight\nC. Reflected light\nD. Moonlight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the cake?
A. Underexposed
B. Just fine
C. Overexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of the cake?
A. Underexposed
B. Just fine
C. Overexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of the cake?\nA. Underexposed\nB. Just fine\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C. Overexposed

[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 740:  50%|▍| 741/1495 [04:1
[Running Accuracy]: 0.7787,[Response]: C. Overexposed<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 741:  50%|▍|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the cake?\nA. Underexposed\nB. Just fine\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C. Overexposed<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting condition good for the headphones in the image?
A. Bright
B. Dim
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting condition good for the headphones in the image?
A. Bright
B. Dim
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting condition good for the headphones in the image?\nA. Bright\nB. Dim\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7787,[Response]: C. Overexposed<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 741:  50%|▍|
[Running Accuracy]: 0.7790,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 742:  50%|▍| 742/1495 [04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting condition good for the headphones in the image?\nA. Bright\nB. Dim\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person sitting in the gazebo in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person sitting in the gazebo in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the person sitting in the gazebo in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7790,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 742:  50%|▍| 743/1495 [04:1
[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 743:  50%|▍| 743/1495 [04:12<04:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person sitting in the gazebo in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?
A. Overexposure
B. Underexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality problems does not exist in this image?
A. Overexposure
B. Underexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality problems does not exist in this image?\nA. Overexposure\nB. Underexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 743:  50%|▍| 744/1495 [04:12<04:1
[Running Accuracy]: 0.7782,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 744:  50%|▍| 744/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?\nA. Overexposure\nB. Underexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?
A. Out of focus
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion of this picture?
A. Out of focus
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion of this picture?\nA. Out of focus\nB. Noise\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7782,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 744:  50%|▍| 745/1495 
[Running Accuracy]: 0.7785,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 745:  50%|▍| 745/1495 [04:13<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?\nA. Out of focus\nB. Noise\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the tire in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the tire in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the tire in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7785,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 745:  50%|▍| 746/1495 [04:13<0
[Running Accuracy]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 746:  50%|▍| 746/1495 [04:13<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the tire in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 746:  50%|▍| 747/1495 [04:13<
[Running Accuracy]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 747:  50%|▍| 747/1495 [04:13<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the texture sharpness in this image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the texture sharpness in this image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the texture sharpness in this image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 747:  50%|▌| 748/1495 [04:13<03:
[Running Accuracy]: 0.7781,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 748:  50%|▌| 748/1495 [04:13<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the texture sharpness in this image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is in the main object in this picture?
A. Ornament
B. Table
C. Sofa
D. Calander
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is in the main object in this picture?
A. Ornament
B. Table
C. Sofa
D. Calander
Answer with the option's letter from the given choices directly.

prompts: [["What is in the main object in this picture?\nA. Ornament\nB. Table\nC. Sofa\nD. Calander\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7781,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 748:  50%|▌| 749/1495 [04:14<04:
[Running Accuracy]: 0.7784,[Response]: A.<|endoftext|>, [Correct Ans]: Ornament, , [Prog]: 749:  50%|▌| 749/1495 [04:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is in the main object in this picture?\nA. Ornament\nB. Table\nC. Sofa\nD. Calander\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7784,[Response]: A.<|endoftext|>, [Correct Ans]: Ornament, , [Prog]: 749:  50%|▌| 750/1495 [04:1
[Running Accuracy]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 750:  50%|▌| 750/1495 [04:14<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall color tone in this image?
A. Greenish
B. Reddish
C. Blueish
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall color tone in this image?
A. Greenish
B. Reddish
C. Blueish
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall color tone in this image?\nA. Greenish\nB. Reddish\nC. Blueish\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 750:  50%|▌| 751/1495 [04:15<04
[Running Accuracy]: 0.7790,[Response]: C.<|endoftext|>, [Correct Ans]: Blueish, , [Prog]: 751:  50%|▌| 751/1495 [04:15
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall color tone in this image?\nA. Greenish\nB. Reddish\nC. Blueish\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image gets over-exposed?
A. The people
B. The chairs
C. The lights
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image gets over-exposed?
A. The people
B. The chairs
C. The lights
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image gets over-exposed?\nA. The people\nB. The chairs\nC. The lights\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7790,[Response]: C.<|endoftext|>, [Correct Ans]: Blueish, , [Prog]: 751:  50%|▌| 752/1495 [04:15
[Running Accuracy]: 0.7793,[Response]: C.<|endoftext|>, [Correct Ans]: The lights, , [Prog]: 752:  50%|▌| 752/1495 [04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image gets over-exposed?\nA. The people\nB. The chairs\nC. The lights\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur caused by the smoke in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any blur caused by the smoke in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any blur caused by the smoke in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7793,[Response]: C.<|endoftext|>, [Correct Ans]: The lights, , [Prog]: 752:  50%|▌| 753/1495 [04
[Running Accuracy]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 753:  50%|▌| 753/1495 [04:15<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur caused by the smoke in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of this image?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. Acceptable\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 753:  50%|▌| 754/1495 [04:16<04:
[Running Accuracy]: 0.7798,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 754:  50%|▌| 754/1495 [04:16<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?\nA. Acceptable\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically pleasing?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically pleasing?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically pleasing?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7798,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 754:  51%|▌| 755/1495 [04:16<04:
[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 755:  51%|▌| 755/1495 [04:16<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically pleasing?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall clarity of this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall clarity of this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7801,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 755:  51%|▌| 756/1495 [04:17<05:0
[Running Accuracy]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 756:  51%|▌| 756/1495 [04:17<05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?
A. The little boy
B. The woman with the camera
C. The man standing on the balance bike
D. The woman in red clothes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of this image?
A. The little boy
B. The woman with the camera
C. The man standing on the balance bike
D. The woman in red clothes
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. The little boy\nB. The woman with the camera\nC. The man standing on the balance bike\nD. The woman in red clothes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 756:  51%|▌| 757/1495 [04:17<04:
[Running Accuracy]: 0.7807,[Response]: C.<|endoftext|>, [Correct Ans]: The man standing on the balance bike, , [Prog]:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?\nA. The little boy\nB. The woman with the camera\nC. The man standing on the balance bike\nD. The woman in red clothes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion occurs on the food eaten by the foxes?
A. Blur
B. Underexposure
C. Noise
D. Compression Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion occurs on the food eaten by the foxes?
A. Blur
B. Underexposure
C. Noise
D. Compression Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion occurs on the food eaten by the foxes?\nA. Blur\nB. Underexposure\nC. Noise\nD. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7807,[Response]: C.<|endoftext|>, [Correct Ans]: The man standing on the balance bike, , [Prog]:
[Running Accuracy]: 0.7810,[Response]: D.<|endoftext|>, [Correct Ans]: Compression Artifacts, , [Prog]: 758:  51%|▌| 7
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion occurs on the food eaten by the foxes?\nA. Blur\nB. Underexposure\nC. Noise\nD. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the kitten emphasized in the center in the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the kitten emphasized in the center in the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the kitten emphasized in the center in the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7810,[Response]: D.<|endoftext|>, [Correct Ans]: Compression Artifacts, , [Prog]: 758:  51%|▌| 7
[Running Accuracy]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 759:  51%|▌| 759/1495 [04:18<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the kitten emphasized in the center in the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the street lamp clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the street lamp clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the street lamp clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 759:  51%|▌| 760/1495 [04:18<04:
[Running Accuracy]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 760:  51%|▌| 760/1495 [04:18<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the street lamp clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 760:  51%|▌| 761/1495 [04:18<03:5
[Running Accuracy]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 761:  51%|▌| 761/1495 [04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stream emphasized in the center in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the stream emphasized in the center in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the stream emphasized in the center in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 761:  51%|▌| 762/1495 [04
[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 762:  51%|▌| 762/1495 [04:18<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stream emphasized in the center in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image has the brightest color?
A. Withered grass
B. Green plants
C. Withered yellow leaves
D. Tree branches
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image has the brightest color?
A. Withered grass
B. Green plants
C. Withered yellow leaves
D. Tree branches
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image has the brightest color?\nA. Withered grass\nB. Green plants\nC. Withered yellow leaves\nD. Tree branches\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 762:  51%|▌| 763/1495 [04:19<03:
[Running Accuracy]: 0.7811,[Response]: B.<|endoftext|>, [Correct Ans]: Green plants, , [Prog]: 763:  51%|▌| 763/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image has the brightest color?\nA. Withered grass\nB. Green plants\nC. Withered yellow leaves\nD. Tree branches\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in this image?
A. Motion blur
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion occurs in this image?
A. Motion blur
B. Out of focus
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion occurs in this image?\nA. Motion blur\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7811,[Response]: B.<|endoftext|>, [Correct Ans]: Green plants, , [Prog]: 763:  51%|▌| 764/1495 [
[Running Accuracy]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 764:  51%|▌| 764/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion occurs in this image?\nA. Motion blur\nB. Out of focus\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the blurriest thing in the image?
A. Pyramid
B. Boardwalk
C. Stone wall
D. Sphinx
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the blurriest thing in the image?
A. Pyramid
B. Boardwalk
C. Stone wall
D. Sphinx
Answer with the option's letter from the given choices directly.

prompts: [["What is the blurriest thing in the image?\nA. Pyramid\nB. Boardwalk\nC. Stone wall\nD. Sphinx\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 764:  51%|▌| 765/1495 [0
[Running Accuracy]: 0.7791,[Response]: B.<|endoftext|>, [Correct Ans]: Pyramid, , [Prog]: 765:  51%|▌| 765/1495 [04:19
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the blurriest thing in the image?\nA. Pyramid\nB. Boardwalk\nC. Stone wall\nD. Sphinx\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7791,[Response]: B.<|endoftext|>, [Correct Ans]: Pyramid, , [Prog]: 765:  51%|▌| 766/1495 [04:20
[Running Accuracy]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 766:  51%|▌| 766/1495 [04:20<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Low
B. Acceptable
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 766:  51%|▌| 767/1495 [04:20<03
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 767:  51%|▌| 767/1495 [04:20<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Low\nB. Acceptable\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition style of the image?
A. Triangular
B. Symmetrical
C. Centric
D. Pyramidal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the composition style of the image?
A. Triangular
B. Symmetrical
C. Centric
D. Pyramidal
Answer with the option's letter from the given choices directly.

prompts: [["What is the composition style of the image?\nA. Triangular\nB. Symmetrical\nC. Centric\nD. Pyramidal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 767:  51%|▌| 768/1495 [04:20<03:
[Running Accuracy]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 768:  51%|▌| 768/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition style of the image?\nA. Triangular\nB. Symmetrical\nC. Centric\nD. Pyramidal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from above?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the light in this image come from above?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the light in this image come from above?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 768:  51%|▌| 769/1495 [0
[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 769:  51%|▌| 769/1495 [04:21<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from above?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur on this sign in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any blur on this sign in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any blur on this sign in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 769:  52%|▌| 770/1495 [04:21<04:
[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 770:  52%|▌| 770/1495 [04:21<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur on this sign in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the plants?
A. Medium
B. Bad
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the plants?
A. Medium
B. Bad
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the plants?\nA. Medium\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 770:  52%|▌| 771/1495 [04:22<05:
[Running Accuracy]: 0.7782,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 771:  52%|▌| 771/1495 [04:22<05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the plants?\nA. Medium\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the background of this picture?
A. Blurry
B. Normal
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the background of this picture?
A. Blurry
B. Normal
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the background of this picture?\nA. Blurry\nB. Normal\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7782,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 771:  52%|▌| 772/1495 [04:22<04
[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 772:  52%|▌| 772/1495 [04:22<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the background of this picture?\nA. Blurry\nB. Normal\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color saturated?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color saturated?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color saturated?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 772:  52%|▌| 773/1495 [04:22<
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 773:  52%|▌| 773/1495 [04:22<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color saturated?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issue does not exist in this image?
A. Noise
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issue does not exist in this image?
A. Noise
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issue does not exist in this image?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 773:  52%|▌| 774/1495 [04:23<04:
[Running Accuracy]: 0.7778,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 774:  52%|▌| 774/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issue does not exist in this image?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which kind of image quality problem does not exist in this image?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which kind of image quality problem does not exist in this image?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which kind of image quality problem does not exist in this image?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7778,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 774:  52%|▌| 775/1495 [
[Running Accuracy]: 0.7768,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 775:  52%|▌| 775/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which kind of image quality problem does not exist in this image?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the primary color of the central position of the image?
A. Brown
B. Green
C. Orange
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the primary color of the central position of the image?
A. Brown
B. Green
C. Orange
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the primary color of the central position of the image?\nA. Brown\nB. Green\nC. Orange\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7768,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 775:  52%|▌| 776/1495 
[Running Accuracy]: 0.7758,[Response]: D.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 776:  52%|▌| 776/1495 [04:23<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the primary color of the central position of the image?\nA. Brown\nB. Green\nC. Orange\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the flowers in this image bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the flowers in this image bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7758,[Response]: D.<|endoftext|>, [Correct Ans]: Orange, , [Prog]: 776:  52%|▌| 777/1495 [04:23<
[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 777:  52%|▌| 777/1495 [04:23<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?
A. Out of focus
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does this image not have?
A. Out of focus
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does this image not have?\nA. Out of focus\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 777:  52%|▌| 778/1495 [04:24<03:4
[Running Accuracy]: 0.7751,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 778:  52%|▌| 778/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image not have?\nA. Out of focus\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7751,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 778:  52%|▌| 779/1495 
[Running Accuracy]: 0.7754,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 779:  52%|▌| 779/1495 [04:24<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the lighting like in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the lighting like in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the lighting like in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7754,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 779:  52%|▌| 780/1495 [04:25<04
[Running Accuracy]: 0.7756,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 780:  52%|▌| 780/1495 [04:25<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the lighting like in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image poorly lit?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image poorly lit?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image poorly lit?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7756,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 780:  52%|▌| 781/1495 [04:25<04:
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 781:  52%|▌| 781/1495 [04:25<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image poorly lit?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 781:  52%|▌| 782/1495 [04:25<04:
[Running Accuracy]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 782:  52%|▌| 782/1495 [04:25<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual feelings does the image evoke?
A. Comfortable
B. Passionate
C. Terrifying
D. Melancholy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feelings does the image evoke?
A. Comfortable
B. Passionate
C. Terrifying
D. Melancholy
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feelings does the image evoke?\nA. Comfortable\nB. Passionate\nC. Terrifying\nD. Melancholy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 782:  52%|▌| 783/1495 [04:26<04:
[Running Accuracy]: 0.7752,[Response]: D.<|endoftext|>, [Correct Ans]: Melancholy, , [Prog]: 783:  52%|▌| 783/1495 [04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual feelings does the image evoke?\nA. Comfortable\nB. Passionate\nC. Terrifying\nD. Melancholy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Sky
B. House
C. Tree
D. Lotus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Sky
B. House
C. Tree
D. Lotus
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Sky\nB. House\nC. Tree\nD. Lotus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7752,[Response]: D.<|endoftext|>, [Correct Ans]: Melancholy, , [Prog]: 783:  52%|▌| 784/1495 [04
[Running Accuracy]: 0.7755,[Response]: D.<|endoftext|>, [Correct Ans]: Lotus, , [Prog]: 784:  52%|▌| 784/1495 [04:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Sky\nB. House\nC. Tree\nD. Lotus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality problem exists in the image?
A. Overexposure
B. Underexposure
C. Noise
D. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality problem exists in the image?
A. Overexposure
B. Underexposure
C. Noise
D. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["Which quality problem exists in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Motion Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7755,[Response]: D.<|endoftext|>, [Correct Ans]: Lotus, , [Prog]: 784:  53%|▌| 785/1495 [04:26<0
[Running Accuracy]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 785:  53%|▌| 785/1495 [04:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality problem exists in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Motion Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have high contrast level?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have high contrast level?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have high contrast level?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 785:  53%|▌| 786/1495 [04:27<0
[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 786:  53%|▌| 786/1495 [04:27<03:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have high contrast level?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man emphasized in the center of the composition in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man emphasized in the center of the composition in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man emphasized in the center of the composition in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 786:  53%|▌| 787/1495 [04:27<03:3
[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 787:  53%|▌| 787/1495 [04:27<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man emphasized in the center of the composition in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dark
B. Bright
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Bright
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Bright\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 787:  53%|▌| 788/1495 [04:27<04:
[Running Accuracy]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 788:  53%|▌| 788/1495 [04:27<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dark\nB. Bright\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blur exists in the phone case in this image?
A. Medium
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blur exists in the phone case in this image?
A. Medium
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blur exists in the phone case in this image?\nA. Medium\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 788:  53%|▌| 789/1495 [04:28<04
[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 789:  53%|▌| 789/1495 [04:28<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blur exists in the phone case in this image?\nA. Medium\nB. Slight\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast level of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 789:  53%|▌| 790/1495 [04:28<
[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 790:  53%|▌| 790/1495 [04:28<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the ship in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the ship in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the ship in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 790:  53%|▌| 791/1495 [04:28<03
[Running Accuracy]: 0.7737,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 791:  53%|▌| 791/1495 [04:28<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the ship in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion about the plants in this picture?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion about the plants in this picture?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion about the plants in this picture?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7737,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 791:  53%|▌| 792/1495 [04:29<04
[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 792:  53%|▌| 792/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion about the plants in this picture?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the humans in this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the humans in this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the humans in this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 792:  53%|▌| 793/1495 [0
[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 793:  53%|▌| 793/1495 [04:29<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the humans in this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the toys in this image?
A. Noise
B. Over-exposure
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the toys in this image?
A. Noise
B. Over-exposure
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the toys in this image?\nA. Noise\nB. Over-exposure\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 793:  53%|▌| 794/1495 [04:29<03
[Running Accuracy]: 0.7746,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 794:  53%|▌| 794/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the toys in this image?\nA. Noise\nB. Over-exposure\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion with this image?
A. Noise
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion with this image?
A. Noise
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion with this image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7746,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 794:  53%|▌| 795/1495 [0
[Running Accuracy]: 0.7736,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 795:  53%|▌| 795/1495 [04:30<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion with this image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the trees?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the trees?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the trees?\nA. Blur\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7736,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 795:  53%|▌| 796/1495 [04:30<0
[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 796:  53%|▌| 796/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the trees?\nA. Blur\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?
A. White
B. Yellow
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. White
B. Yellow
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. White\nB. Yellow\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 796:  53%|▌| 797/1495
[Running Accuracy]: 0.7742,[Response]: C.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 797:  53%|▌| 797/1495 [04:31<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?\nA. White\nB. Yellow\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there overexposure in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there overexposure in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there overexposure in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7742,[Response]: C.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 797:  53%|▌| 798/1495 [04:31<03:
[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 798:  53%|▌| 798/1495 [04:31<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there overexposure in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 798:  53%|▌| 799/1495 [04:31<03:4
[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 799:  53%|▌| 799/1495 [04:31<03:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the phones emphasized in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the phones emphasized in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the phones emphasized in the center of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A. No

[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 799:  54%|▌| 800/1495 [04:31<03:4
[Running Accuracy]: 0.7738,[Response]: A. No<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 800:  54%|▌| 800/1495 [04:31<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the phones emphasized in the center of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A. No<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What part of the image is the focus?
A. Monster's claws
B. Monster's mouth
C. Monster's tail
D. Monster's whiskers
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What part of the image is the focus?
A. Monster's claws
B. Monster's mouth
C. Monster's tail
D. Monster's whiskers
Answer with the option's letter from the given choices directly.

prompts: [["What part of the image is the focus?\nA. Monster's claws\nB. Monster's mouth\nC. Monster's tail\nD. Monster's whiskers\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7738,[Response]: A. No<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 800:  54%|▌| 801/1495 [04:32<
[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Monster's mouth, , [Prog]: 801:  54%|▌| 801/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What part of the image is the focus?\nA. Monster's claws\nB. Monster's mouth\nC. Monster's tail\nD. Monster's whiskers\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers on the roof in this picture vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers on the roof in this picture vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers on the roof in this picture vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Monster's mouth, , [Prog]: 801:  54%|▌| 802/149
[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 802:  54%|▌| 802/1495 [04:32<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers on the roof in this picture vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blurring due to motion in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any blurring due to motion in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any blurring due to motion in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 802:  54%|▌| 803/1495 [04:32<03:
[Running Accuracy]: 0.7746,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 803:  54%|▌| 803/1495 [04:32<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blurring due to motion in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7746,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 803:  54%|▌| 804/1495 [04:33<03:
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 804:  54%|▌| 804/1495 [04:33<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 804:  54%|▌| 805/1495 [04:33<03
[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 805:  54%|▌| 805/1495 [04:33<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vivid?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the flowers in this image vivid?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the flowers in this image vivid?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 805:  54%|▌| 806/1495 [04:33<0
[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 806:  54%|▌| 806/1495 [04:33<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the flowers in this image vivid?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?
A. Dark
B. Fresh
C. Bright
D. Happy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the image give?
A. Dark
B. Fresh
C. Bright
D. Happy
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the image give?\nA. Dark\nB. Fresh\nC. Bright\nD. Happy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 806:  54%|▌| 807/1495 [04:33<03:
[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 807:  54%|▌| 807/1495 [04:33<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?\nA. Dark\nB. Fresh\nC. Bright\nD. Happy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 807:  54%|▌| 808/1495 [04:34<03
[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 808:  54%|▌| 808/1495 [04:34<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 808:  54%|▌| 809/1495 [04:34<03:
[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 809:  54%|▌| 809/1495 [04:34<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 809:  54%|▌| 810/1495 [04:35<04:
[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 810:  54%|▌| 810/1495 [04:35<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear or blurry?
A. Clear
B. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear or blurry?
A. Clear
B. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear or blurry?\nA. Clear\nB. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 810:  54%|▌| 811/1495 [04:35<04:
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 811:  54%|▌| 811/1495 [04:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear or blurry?\nA. Clear\nB. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?
A. Plants
B. Building
C. Statue
D. Woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of this image?
A. Plants
B. Building
C. Statue
D. Woman
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. Plants\nB. Building\nC. Statue\nD. Woman\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 811:  54%|▌| 812/1495 [04:35<
[Running Accuracy]: 0.7734,[Response]: C.<|endoftext|>, [Correct Ans]: Statue, , [Prog]: 812:  54%|▌| 812/1495 [04:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?\nA. Plants\nB. Building\nC. Statue\nD. Woman\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography effects were used in the image?
A. Motion blur
B. Shallow depth of field
C. Black and white filter
D. Long exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What photography effects were used in the image?
A. Motion blur
B. Shallow depth of field
C. Black and white filter
D. Long exposure
Answer with the option's letter from the given choices directly.

prompts: [["What photography effects were used in the image?\nA. Motion blur\nB. Shallow depth of field\nC. Black and white filter\nD. Long exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7734,[Response]: C.<|endoftext|>, [Correct Ans]: Statue, , [Prog]: 812:  54%|▌| 813/1495 [04:36<
[Running Accuracy]: 0.7737,[Response]: C.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 813:  54%|▌| 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography effects were used in the image?\nA. Motion blur\nB. Shallow depth of field\nC. Black and white filter\nD. Long exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?
A. Fair
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Fair
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Fair\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7737,[Response]: C.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 813:  54%|▌| 
[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 814:  54%|▌| 814/1495 [04:36<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?\nA. Fair\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 814:  55%|▌| 815/1495 [04:37<04
[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 815:  55%|▌| 815/1495 [04:37<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 815:  55%|▌| 816/1495 [04:37<04:
[Running Accuracy]: 0.7745,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 816:  55%|▌| 816/1495 [04:37<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image's clarity?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image's clarity?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image's clarity?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7745,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 816:  55%|▌| 817/1495 [04:37<04
[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 817:  55%|▌| 817/1495 [04:37<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image's clarity?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the wall painting on the middle top of the image?
A. Noise
B. Over-exposure
C. Low light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the wall painting on the middle top of the image?
A. Noise
B. Over-exposure
C. Low light
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the wall painting on the middle top of the image?\nA. Noise\nB. Over-exposure\nC. Low light\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7748,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 817:  55%|▌| 818/1495 [04:38<04:
[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 818:  55%|▌| 818/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of the wall painting on the middle top of the image?\nA. Noise\nB. Over-exposure\nC. Low light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 818:  55%|▌| 819/1495 
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 819:  55%|▌| 819/1495 [04:38<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sharpness of this image high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sharpness of this image high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the sharpness of this image high?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 819:  55%|▌| 820/1495 [04:39<04:
[Running Accuracy]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 820:  55%|▌| 820/1495 [04:39<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sharpness of this image high?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 820:  55%|▌| 821/1495 [04:39<04:
[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 821:  55%|▌| 821/1495 [04:39<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Clear\nB. Normal\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sharpness of this image high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sharpness of this image high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the sharpness of this image high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 821:  55%|▌| 822/1495 [04:39<0
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 822:  55%|▌| 822/1495 [04:39<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sharpness of this image high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 822:  55%|▌| 823/1495 [04:40<03:
[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 823:  55%|▌| 823/1495 [04:40<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Colorful
B. Normal
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Normal
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Normal\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 823:  55%|▌| 824/1495 [04:40<03:3
[Running Accuracy]: 0.7731,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 824:  55%|▌| 824/1495 [04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Colorful\nB. Normal\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure issue in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an underexposure issue in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure issue in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 824:  55%|▌| 825/1495 [04:4
[Running Accuracy]: 0.7733,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 825:  55%|▌| 825/1495 [04:40<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an underexposure issue in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion troubles the quality of the image?
A. Noise
B. Blur
C. Compression Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion troubles the quality of the image?
A. Noise
B. Blur
C. Compression Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What distortion troubles the quality of the image?\nA. Noise\nB. Blur\nC. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7733,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 825:  55%|▌| 826/1495 [04:41<04:2
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 826:  55%|▌| 826/1495 [04:41<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion troubles the quality of the image?\nA. Noise\nB. Blur\nC. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?
A. vehicle
B. sky
C. plants
D. building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of the image?
A. vehicle
B. sky
C. plants
D. building
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. vehicle\nB. sky\nC. plants\nD. building\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 826:  55%|▌| 827/1495 [04:41<03
[Running Accuracy]: 0.7739,[Response]: D.<|endoftext|>, [Correct Ans]: building, , [Prog]: 827:  55%|▌| 827/1495 [04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?\nA. vehicle\nB. sky\nC. plants\nD. building\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the wall and ground?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the wall and ground?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the wall and ground?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7739,[Response]: D.<|endoftext|>, [Correct Ans]: building, , [Prog]: 827:  55%|▌| 828/1495 [04:4
[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 828:  55%|▌| 828/1495 [04:41<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the wall and ground?\nA. Acceptable\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Normal
B. Dull
C. Colorful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Normal
B. Dull
C. Colorful
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Normal\nB. Dull\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 828:  55%|▌| 829/1495 [04:42<03
[Running Accuracy]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 829:  55%|▌| 829/1495 [04:42<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Normal\nB. Dull\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you assess the lighting conditions of the background in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you assess the lighting conditions of the background in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How would you assess the lighting conditions of the background in this image?\nA. Medium\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 829:  56%|▌| 830/1495 [04:42<03
[Running Accuracy]: 0.7747,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 830:  56%|▌| 830/1495 [04:42<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you assess the lighting conditions of the background in this image?\nA. Medium\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees in this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the trees in this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the trees in this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7747,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 830:  56%|▌| 831/1495 [04:43<04
[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 831:  56%|▌| 831/1495 [04:43<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the trees in this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7750,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 831:  56%|▌| 832/1495 [04:43<04:
[Running Accuracy]: 0.7740,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 832:  56%|▌| 832/1495 [04:43<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness exists in the big tree in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blurriness exists in the big tree in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blurriness exists in the big tree in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7740,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 832:  56%|▌| 833/1495 [04:43<03
[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 833:  56%|▌| 833/1495 [04:43<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness exists in the big tree in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the human faces in this image look realistic or computer-generated?
A. Realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the human faces in this image look realistic or computer-generated?
A. Realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.

prompts: [["Do the human faces in this image look realistic or computer-generated?\nA. Realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 833:  56%|▌| 834/1495 [04:43<
[Running Accuracy]: 0.7746,[Response]: B.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 834:  56%|▌| 834/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the human faces in this image look realistic or computer-generated?\nA. Realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, is the monster emphasized in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, is the monster emphasized in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, is the monster emphasized in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7746,[Response]: B.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 834:  56%|▌| 835/
[Running Accuracy]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 835:  56%|▌| 835/1495 [04:44<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, is the monster emphasized in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the stone contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the stone contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the stone contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 835:  56%|▌| 836/1495 [04:44<04:
[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 836:  56%|▌| 836/1495 [04:44<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the stone contain rich texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7751,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 836:  56%|▌| 837/1495 [04:45<04:
[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 837:  56%|▌| 837/1495 [04:45<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the motion blur in this image?
A. No Motion Blur
B. Weak
C. Strong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the motion blur in this image?
A. No Motion Blur
B. Weak
C. Strong
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the motion blur in this image?\nA. No Motion Blur\nB. Weak\nC. Strong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 837:  56%|▌| 838/1495 [04:45<04:3
[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 838:  56%|▌| 838/1495 [04:45<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the motion blur in this image?\nA. No Motion Blur\nB. Weak\nC. Strong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the circle in the left look pleasant or annoying?
A. Pleasant
B. Annoying
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the circle in the left look pleasant or annoying?
A. Pleasant
B. Annoying
Answer with the option's letter from the given choices directly.

prompts: [["Does the circle in the left look pleasant or annoying?\nA. Pleasant\nB. Annoying\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 838:  56%|▌| 839/1495 [04:45<04
[Running Accuracy]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Annoying, , [Prog]: 839:  56%|▌| 839/1495 [04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the circle in the left look pleasant or annoying?\nA. Pleasant\nB. Annoying\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Annoying, , [Prog]: 839:  56%|▌| 840/1495 [04:4
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 840:  56%|▌| 840/1495 [04:46<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?
A. Too low
B. Too high
C. Just fine
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast level of the image?
A. Too low
B. Too high
C. Just fine
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level of the image?\nA. Too low\nB. Too high\nC. Just fine\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 840:  56%|▌| 841/1495 [04:46<04:
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Too high, , [Prog]: 841:  56%|▌| 841/1495 [04:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?\nA. Too low\nB. Too high\nC. Just fine\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Too high, , [Prog]: 841:  56%|▌| 842/1495 [04:4
[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 842:  56%|▌| 842/1495 [04:46<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Motion blur
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Motion blur
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Motion blur\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 842:  56%|▌| 843/1495 [04:47<04:
[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 843:  56%|▌| 843/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Motion blur\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the sofas in this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the sofas in this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the sofas in this picture have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 843:  56%|▌| 844/1495 
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 844:  56%|▌| 844/1495 [04:48<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the sofas in this picture have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 844:  57%|▌| 845/1495 [04:48<05:
[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 845:  57%|▌| 845/1495 [04:48<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the scenery outside the window in this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the scenery outside the window in this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the scenery outside the window in this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 845:  57%|▌| 846/1495 [04:48<
[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 846:  57%|▌| 846/1495 [04:48<04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the scenery outside the window in this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image include professional background bokeh?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image include professional background bokeh?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image include professional background bokeh?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 846:  57%|▌| 847/1495 [04:49<04
[Running Accuracy]: 0.7745,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 847:  57%|▌| 847/1495 [04:49<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image include professional background bokeh?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Poor\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7745,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 847:  57%|▌| 848/1495 [04:49<03:
[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 848:  57%|▌| 848/1495 [04:49<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Poor\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 848:  57%|▌| 849/1495 [04:49<03
[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 849:  57%|▌| 849/1495 [04:49<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the wall rich in texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the wall rich in texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the wall rich in texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 849:  57%|▌| 850/1495 [04:50<03:
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 850:  57%|▌| 850/1495 [04:50<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the wall rich in texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most prominent color in the image?
A. Red
B. Yellow
C. Blue
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most prominent color in the image?
A. Red
B. Yellow
C. Blue
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Red\nB. Yellow\nC. Blue\nD. Black\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 850:  57%|▌| 851/1495 [04:50<03:
[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 851:  57%|▌| 851/1495 [04:50<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most prominent color in the image?\nA. Red\nB. Yellow\nC. Blue\nD. Black\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image?
A. Pink flower
B. Orange flower
C. Butterfly
D. Leaf
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the image?
A. Pink flower
B. Orange flower
C. Butterfly
D. Leaf
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the image?\nA. Pink flower\nB. Orange flower\nC. Butterfly\nD. Leaf\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 851:  57%|▌| 852/1495 [04:50<03
[Running Accuracy]: 0.7746,[Response]: C.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 852:  57%|▌| 852/1495 [04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image?\nA. Pink flower\nB. Orange flower\nC. Butterfly\nD. Leaf\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?
A. Noise
B. Out of focus
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is not a main distortion in this picture?
A. Noise
B. Out of focus
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is not a main distortion in this picture?\nA. Noise\nB. Out of focus\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7746,[Response]: C.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 852:  57%|▌| 853/1495 [04:
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 853:  57%|▌| 853/1495 [04:51<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?\nA. Noise\nB. Out of focus\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Dull
B. Colorful
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Dull
B. Colorful
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Dull\nB. Colorful\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 853:  57%|▌| 854/1495 [04:51<0
[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 854:  57%|▌| 854/1495 [04:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Dull\nB. Colorful\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual experience?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a refreshing visual experience?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing visual experience?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7740,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 854:  57%|▌| 855/1495 [04:5
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 855:  57%|▌| 855/1495 [04:51<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual experience?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the aesthetic quality of this image?
A. Good
B. Poor
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the aesthetic quality of this image?
A. Good
B. Poor
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the aesthetic quality of this image?\nA. Good\nB. Poor\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 855:  57%|▌| 856/1495 [04:51<03:0
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 856:  57%|▌| 856/1495 [04:51<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the aesthetic quality of this image?\nA. Good\nB. Poor\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Noise
B. Blur
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Noise
B. Blur
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Noise\nB. Blur\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 856:  57%|▌| 857/1495 [04:52<03
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 857:  57%|▌| 857/1495 [04:52<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Noise\nB. Blur\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 857:  57%|▌| 858/1495 [04:52<04
[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 858:  57%|▌| 858/1495 [04:52<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Somewhat blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Somewhat blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Somewhat blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 858:  57%|▌| 859/1495 [04:53<
[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 859:  57%|▌| 859/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Somewhat blurry\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?
A. Fence
B. Pedestrian
C. Cyclist
D. Car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focus?
A. Fence
B. Pedestrian
C. Cyclist
D. Car
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focus?\nA. Fence\nB. Pedestrian\nC. Cyclist\nD. Car\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7730,[Response]: A.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 859:  58%|▌| 860/149
[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Cyclist, , [Prog]: 860:  58%|▌| 860/1495 [04:53
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?\nA. Fence\nB. Pedestrian\nC. Cyclist\nD. Car\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Cyclist, , [Prog]: 860:  58%|▌| 861/1495 [04:53
[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 861:  58%|▌| 861/1495 [04:53<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject fully covered in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject fully covered in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject fully covered in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 861:  58%|▌| 862/1495 [04:53<03
[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 862:  58%|▌| 862/1495 [04:53<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject fully covered in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 862:  58%|▌| 863/1495 [04:54<03:1
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 863:  58%|▌| 863/1495 [04:54<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any compression distortion in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any compression distortion in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any compression distortion in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 863:  58%|▌| 864/1495 [04:54<03
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 864:  58%|▌| 864/1495 [04:54<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any compression distortion in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the image?
A. Brown
B. Green
C. Purple
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color scheme of the image?
A. Brown
B. Green
C. Purple
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color scheme of the image?\nA. Brown\nB. Green\nC. Purple\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 864:  58%|▌| 865/1495 [04:54<03:0
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 865:  58%|▌| 865/1495 [04:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the image?\nA. Brown\nB. Green\nC. Purple\nD. Yellow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Acceptable
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Acceptable
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Acceptable\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 865:  58%|▌| 866/1495 [04:55<0
[Running Accuracy]: 0.7725,[Response]: A.<|endoftext|>, [Correct Ans]: Excellent, , [Prog]: 866:  58%|▌| 866/1495 [04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Acceptable\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?
A. red
B. gray
C. blue
D. white
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. red
B. gray
C. blue
D. white
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. red\nB. gray\nC. blue\nD. white\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7725,[Response]: A.<|endoftext|>, [Correct Ans]: Excellent, , [Prog]: 866:  58%|▌| 867/1495 [04:
[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: red, , [Prog]: 867:  58%|▌| 867/1495 [04:55<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest color in this image?\nA. red\nB. gray\nC. blue\nD. white\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: red, , [Prog]: 867:  58%|▌| 868/1495 [04:56<03:
[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 868:  58%|▌| 868/1495 [04:56<03:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 868:  58%|▌| 869/1495 [04:56<03:3
[Running Accuracy]: 0.7710,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 869:  58%|▌| 869/1495 [04:56<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background vegetation in the image?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background vegetation in the image?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background vegetation in the image?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7710,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 869:  58%|▌| 870/1495 [04:56<03:
[Running Accuracy]: 0.7701,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 870:  58%|▌| 870/1495 [04:56<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background vegetation in the image?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the objects in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the objects in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the objects in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7701,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 870:  58%|▌| 871/1495 [04:56<
[Running Accuracy]: 0.7704,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 871:  58%|▌| 871/1495 [04:56<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the objects in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the noise level of the cat in this image?
A. Acceptable
B. Weak
C. Srong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the noise level of the cat in this image?
A. Acceptable
B. Weak
C. Srong
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the noise level of the cat in this image?\nA. Acceptable\nB. Weak\nC. Srong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7704,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 871:  58%|▌| 872/1495 [04:57<03:2
[Running Accuracy]: 0.7706,[Response]: C.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 872:  58%|▌| 872/1495 [04:57<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the noise level of the cat in this image?\nA. Acceptable\nB. Weak\nC. Srong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7706,[Response]: C.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 872:  58%|▌| 873/1495 [04:57<0
[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 873:  58%|▌| 873/1495 [04:57<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the leaves in the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the leaves in the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the leaves in the image?\nA. Good\nB. Moderate\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 873:  58%|▌| 874/1495 [04:57<03:
[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 874:  58%|▌| 874/1495 [04:57<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the leaves in the image?\nA. Good\nB. Moderate\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the tree in the image?
A. Very blurry
B. Not blurry at all
C. Somewhat blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the tree in the image?
A. Very blurry
B. Not blurry at all
C. Somewhat blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the tree in the image?\nA. Very blurry\nB. Not blurry at all\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 874:  59%|▌| 875/1495 [04:58<03
[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 875:  59%|▌| 875/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the tree in the image?\nA. Very blurry\nB. Not blurry at all\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the person in the left?
A. Acceptable
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the person in the left?
A. Acceptable
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the person in the left?\nA. Acceptable\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 875:  59%|▌| 876/149
[Running Accuracy]: 0.7717,[Response]: B.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 876:  59%|▌| 876/1495 [04:58<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the person in the left?\nA. Acceptable\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7717,[Response]: B.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 876:  59%|▌| 877/1495 [04:58<03:
[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 877:  59%|▌| 877/1495 [04:58<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure level of the image?
A. Underexposed
B. Moderate
C. Overexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure level of the image?
A. Underexposed
B. Moderate
C. Overexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure level of the image?\nA. Underexposed\nB. Moderate\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 877:  59%|▌| 878/1495 [04:59<03:
[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 878:  59%|▌| 878/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure level of the image?\nA. Underexposed\nB. Moderate\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color richness of the image high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color richness of the image high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color richness of the image high?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7722,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 878:  59%|▌| 879/1495 [
[Running Accuracy]: 0.7713,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 879:  59%|▌| 879/1495 [04:59<03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color richness of the image high?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7713,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 879:  59%|▌| 880/1495 [04:59<03:1
[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 880:  59%|▌| 880/1495 [04:59<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 880:  59%|▌| 881/1495 [05:00<04:
[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 881:  59%|▌| 881/1495 [05:00<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 881:  59%|▌| 882/1495 [05:00<
[Running Accuracy]: 0.7721,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 882:  59%|▌| 882/1495 [05:00<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting of the train in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting of the train in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting of the train in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7721,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 882:  59%|▌| 883/1495 [05:01<03
[Running Accuracy]: 0.7724,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 883:  59%|▌| 883/1495 [05:01<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting of the train in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7724,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 883:  59%|▌| 884/1495 [05:01<
[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 884:  59%|▌| 884/1495 [05:01<03:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distotion for the trees on the top right in this image?
A. Noise
B. Over-exposure
C. Low light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distotion for the trees on the top right in this image?
A. Noise
B. Over-exposure
C. Low light
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distotion for the trees on the top right in this image?\nA. Noise\nB. Over-exposure\nC. Low light\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 884:  59%|▌| 885/1495 [05:01<03:2
[Running Accuracy]: 0.7729,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 885:  59%|▌| 885/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distotion for the trees on the top right in this image?\nA. Noise\nB. Over-exposure\nC. Low light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7729,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 885:  59%|▌| 886/1495 
[Running Accuracy]: 0.7731,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 886:  59%|▌| 886/1495 [05:01<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7731,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 886:  59%|▌| 887/1495 [05:02<0
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 887:  59%|▌| 887/1495 [05:02<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?
A. Out of focus
B. Overexposed
C. Underexposed
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in this image?
A. Out of focus
B. Overexposed
C. Underexposed
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in this image?\nA. Out of focus\nB. Overexposed\nC. Underexposed\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 887:  59%|▌| 888/1495 [05:02<03
[Running Accuracy]: 0.7725,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 888:  59%|▌| 888/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?\nA. Out of focus\nB. Overexposed\nC. Underexposed\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the window brighter than the armchair in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the window brighter than the armchair in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the window brighter than the armchair in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7725,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 888:  59%|▌| 889/1495 [0
[Running Accuracy]: 0.7728,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 889:  59%|▌| 889/1495 [05:02<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the window brighter than the armchair in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color richness in the image?
A. Rich
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color richness in the image?
A. Rich
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color richness in the image?\nA. Rich\nB. Monotonous\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7728,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 889:  60%|▌| 890/1495 [05:03<03:
[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 890:  60%|▌| 890/1495 [05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color richness in the image?\nA. Rich\nB. Monotonous\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any blur in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 890:  60%|▌| 891/1495 [05
[Running Accuracy]: 0.7722,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 891:  60%|▌| 891/1495 [05:03<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any blur in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image overexposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image overexposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image overexposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7722,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 891:  60%|▌| 892/1495 [05:03<03:
[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 892:  60%|▌| 892/1495 [05:03<03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image overexposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the butterfly in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the butterfly in the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the butterfly in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7724,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 892:  60%|▌| 893/1495 [05:04<03:0
[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 893:  60%|▌| 893/1495 [05:04<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the butterfly in the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man holding a beer glass emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man holding a beer glass emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the man holding a beer glass emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7727,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 893:  60%|▌| 894/1495 [05:04<03
[Running Accuracy]: 0.7729,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 894:  60%|▌| 894/1495 [05:04<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man holding a beer glass emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7729,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 894:  60%|▌| 895/1495 [05:04<03:
[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 895:  60%|▌| 895/1495 [05:04<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?
A. Tree
B. Building
C. Car
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, which object is emphasized in the center?
A. Tree
B. Building
C. Car
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. Tree\nB. Building\nC. Car\nD. Sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 895:  60%|▌| 896/1495 [05:05<03:
[Running Accuracy]: 0.7734,[Response]: C.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 896:  60%|▌| 896/1495 [05:05<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?\nA. Tree\nB. Building\nC. Car\nD. Sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality problems does the image have?
A. Out of focus
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality problems does the image have?
A. Out of focus
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality problems does the image have?\nA. Out of focus\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7734,[Response]: C.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 896:  60%|▌| 897/1495 [05:05<03:
[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 897:  60%|▌| 897/1495 [05:05<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of quality problems does the image have?\nA. Out of focus\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image too dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image too dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image too dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 897:  60%|▌| 898/1495 [05:05<0
[Running Accuracy]: 0.7728,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 898:  60%|▌| 898/1495 [05:05<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image too dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the Buddha's head in the image rich?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the Buddha's head in the image rich?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the Buddha's head in the image rich?\nA. Monotonous\nB. Rich\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7728,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 898:  60%|▌| 899/1495 [05:05<03:
[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 899:  60%|▌| 899/1495 [05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the Buddha's head in the image rich?\nA. Monotonous\nB. Rich\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bowl aesthetically pleasing?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bowl aesthetically pleasing?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bowl aesthetically pleasing?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7720,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 899:  60%|▌| 900/1495 [05
[Running Accuracy]: 0.7722,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 900:  60%|▌| 900/1495 [05:06<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bowl aesthetically pleasing?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7722,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 900:  60%|▌| 901/1495 [05:06<03:
[Running Accuracy]: 0.7725,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 901:  60%|▌| 901/1495 [05:06<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the subject in the image?
A. Brown
B. Red
C. Green
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the subject in the image?
A. Brown
B. Red
C. Green
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the subject in the image?\nA. Brown\nB. Red\nC. Green\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7725,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 901:  60%|▌| 902/1495 [05:06<03:
[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 902:  60%|▌| 902/1495 [05:06<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the subject in the image?\nA. Brown\nB. Red\nC. Green\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does the people in this image suffer most?
A. Compression Artifacts
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does the people in this image suffer most?
A. Compression Artifacts
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does the people in this image suffer most?\nA. Compression Artifacts\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 902:  60%|▌| 903/1495 [05:07<0
[Running Accuracy]: 0.7730,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 903:  60%|▌| 903/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does the people in this image suffer most?\nA. Compression Artifacts\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Good
B. Medium
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7730,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 903:  60%|▌| 904/1495 
[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 904:  60%|▌| 904/1495 [05:07<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?\nA. Good\nB. Medium\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image composition?
A. A red car
B. A man carrying a bag on his back
C. A man with a black headscarf
D. A black car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the image composition?
A. A red car
B. A man carrying a bag on his back
C. A man with a black headscarf
D. A black car
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the image composition?\nA. A red car\nB. A man carrying a bag on his back\nC. A man with a black headscarf\nD. A black car\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 904:  61%|▌| 905/1495 [05:07<03
[Running Accuracy]: 0.7735,[Response]: C.<|endoftext|>, [Correct Ans]: A man with a black headscarf, , [Prog]: 905:  6
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image composition?\nA. A red car\nB. A man carrying a bag on his back\nC. A man with a black headscarf\nD. A black car\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7735,[Response]: C.<|endoftext|>, [Correct Ans]: A man with a black headscarf, , [Prog]: 905:  6
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 906:  61%|▌| 906/1495 [05:08<03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 906:  61%|▌| 907/1495 [05:08<03:0
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 907:  61%|▌| 907/1495 [05:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 907:  61%|▌| 908/1495 [05:08<
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 908:  61%|▌| 908/1495 [05:08<03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 908:  61%|▌| 909/1495 [05:09<03:0
[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 909:  61%|▌| 909/1495 [05:09<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?
A. Underexposed
B. Just fine
C. Overexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of this image?
A. Underexposed
B. Just fine
C. Overexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of this image?\nA. Underexposed\nB. Just fine\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 909:  61%|▌| 910/1495 [05:09<03:
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 910:  61%|▌| 910/1495 [05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?\nA. Underexposed\nB. Just fine\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 910:  61%|▌| 911/1495 [05:
[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 911:  61%|▌| 911/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 911:  61%|▌| 912/
[Running Accuracy]: 0.7741,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 912:  61%|▌| 912/1495 [05:10<04:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the texture realness in this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the texture realness in this image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the texture realness in this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7741,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 912:  61%|▌| 913/1495 [05:10<03:
[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 913:  61%|▌| 913/1495 [05:10<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the texture realness in this image?\nA. Fair\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7744,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 913:  61%|▌| 914/1495 [05:11<03
[Running Accuracy]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 914:  61%|▌| 914/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 914:  61%|▌| 915/1
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 915:  61%|▌| 915/1495 [05:11<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 915:  61%|▌| 916/1495 [05:12<04:
[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 916:  61%|▌| 916/1495 [05:12<04:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the animated character in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the animated character in this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the animated character in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 916:  61%|▌| 917/1495 [05:12<03:5
[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 917:  61%|▌| 917/1495 [05:12<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the animated character in this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7743,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 917:  61%|▌| 918/1495 [05:12<03
[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 918:  61%|▌| 918/1495 [05:12<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the dog's fur in the image?
A. Clear
B. Blurry
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the dog's fur in the image?
A. Clear
B. Blurry
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the dog's fur in the image?\nA. Clear\nB. Blurry\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7734,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 918:  61%|▌| 919/1495 [05:13<
[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 919:  61%|▌| 919/1495 [05:13<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the dog's fur in the image?\nA. Clear\nB. Blurry\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7726,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 919:  62%|▌| 920/1495 [05:13<
[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 920:  62%|▌| 920/1495 [05:13<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pillow in the picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pillow in the picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pillow in the picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 920:  62%|▌| 921/1495 [05:13<03:
[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 921:  62%|▌| 921/1495 [05:13<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pillow in the picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7731,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 921:  62%|▌| 922/1495 [05:14<03:
[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 922:  62%|▌| 922/1495 [05:14<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 922:  62%|▌| 923/1495 [05:14<0
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 923:  62%|▌| 923/1495 [05:14<03:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the hairs of the rabbit clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the hairs of the rabbit clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the hairs of the rabbit clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 923:  62%|▌| 924/1495 [05:15<03:3
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 924:  62%|▌| 924/1495 [05:15<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the hairs of the rabbit clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there a clear subject in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there a clear subject in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there a clear subject in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 924:  62%|▌| 925/1495 [05:15<03:
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 925:  62%|▌| 925/1495 [05:15<03:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there a clear subject in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this image?
A. Bright
B. Fair
C. Dim
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this image?
A. Bright
B. Fair
C. Dim
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this image?\nA. Bright\nB. Fair\nC. Dim\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 925:  62%|▌| 926/1495 [05:16<04:1
[Running Accuracy]: 0.7732,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 926:  62%|▌| 926/1495 [05:16<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this image?\nA. Bright\nB. Fair\nC. Dim\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7732,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 926:  62%|▌| 927/1495 [05:16<
[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 927:  62%|▌| 927/1495 [05:16<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the road sign in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the road sign in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the road sign in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 927:  62%|▌| 928/1495 [05:16<03
[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 928:  62%|▌| 928/1495 [05:16<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the road sign in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Fair
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Fair
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Fair\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7726,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 928:  62%|▌| 929/1495 [05:17<03
[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 929:  62%|▌| 929/1495 [05:17<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Fair\nB. Dark\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems are not present in the image?
A. Excessive noise
B. Out of focus
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems are not present in the image?
A. Excessive noise
B. Out of focus
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What problems are not present in the image?\nA. Excessive noise\nB. Out of focus\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7729,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 929:  62%|▌| 930/1495 [05:17<
[Running Accuracy]: 0.7720,[Response]: C.<|endoftext|>, [Correct Ans]: Excessive noise, , [Prog]: 930:  62%|▌| 930/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems are not present in the image?\nA. Excessive noise\nB. Out of focus\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image photo-realistic?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7720,[Response]: C.<|endoftext|>, [Correct Ans]: Excessive noise, , [Prog]: 930:  62%|▌| 931/149
[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 931:  62%|▌| 931/1495 [05:17<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting terrible in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting terrible in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting terrible in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 931:  62%|▌| 932/1495 [05:18<03:3
[Running Accuracy]: 0.7715,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 932:  62%|▌| 932/1495 [05:18<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting terrible in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7715,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 932:  62%|▌| 933/1495 [05:18<03:2
[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 933:  62%|▌| 933/1495 [05:18<03:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the human in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the human in this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 933:  62%|▌| 934/1495 [05:18<03:1
[Running Accuracy]: 0.7709,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 934:  62%|▌| 934/1495 [05:18<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human in this image?\nA. Dark\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of weather-related distortion happens in this image?
A. Rain
B. Snow
C. Fog
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of weather-related distortion happens in this image?
A. Rain
B. Snow
C. Fog
Answer with the option's letter from the given choices directly.

prompts: [["What kind of weather-related distortion happens in this image?\nA. Rain\nB. Snow\nC. Fog\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7709,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 934:  63%|▋| 935/1495 [05:19<03
[Running Accuracy]: 0.7711,[Response]: B.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 935:  63%|▋| 935/1495 [05:19<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of weather-related distortion happens in this image?\nA. Rain\nB. Snow\nC. Fog\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you assess the lighting conditions of the singer in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you assess the lighting conditions of the singer in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How would you assess the lighting conditions of the singer in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7711,[Response]: B.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 935:  63%|▋| 936/1495 [05:19<03
[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 936:  63%|▋| 936/1495 [05:19<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you assess the lighting conditions of the singer in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Motion blur
B. Noise
C. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Motion blur
B. Noise
C. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Motion blur\nB. Noise\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 936:  63%|▋| 937/1495 [05:19<03
[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 937:  63%|▋| 937/1495 [05:19<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Motion blur\nB. Noise\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the soccer players in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the soccer players in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the soccer players in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 937:  63%|▋| 938/1495 [05:20<0
[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 938:  63%|▋| 938/1495 [05:20<03:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the soccer players in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?
A. Medium
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Medium
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Medium\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7719,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 938:  63%|▋| 939/1495 [05:20<03:0
[Running Accuracy]: 0.7710,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 939:  63%|▋| 939/1495 [05:20<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?\nA. Medium\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the red sculpture emphasized in the center in the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the red sculpture emphasized in the center in the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the red sculpture emphasized in the center in the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7710,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 939:  63%|▋| 940/1495 [05:20<
[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 940:  63%|▋| 940/1495 [05:20<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the red sculpture emphasized in the center in the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there noise problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there noise problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there noise problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7713,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 940:  63%|▋| 941/1495 [05:21<02:
[Running Accuracy]: 0.7705,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 941:  63%|▋| 941/1495 [05:21<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there noise problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the legs of the people in the image the darkest area?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the legs of the people in the image the darkest area?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the legs of the people in the image the darkest area?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7705,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 941:  63%|▋| 942/1495 [05:21<02:
[Running Accuracy]: 0.7707,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 942:  63%|▋| 942/1495 [05:21<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the legs of the people in the image the darkest area?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the building in this image?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the building in this image?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the building in this image?\nA. Acceptable\nB. Excellent\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7707,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 942:  63%|▋| 943/1495 [05:21<02:
[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 943:  63%|▋| 943/1495 [05:21<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the building in this image?\nA. Acceptable\nB. Excellent\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the yellow street sign noisy in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the yellow street sign noisy in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the yellow street sign noisy in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 943:  63%|▋| 944/1495 [05:21<02:
[Running Accuracy]: 0.7712,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 944:  63%|▋| 944/1495 [05:21<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the yellow street sign noisy in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of the clock in this image?
A. Under-exposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of the clock in this image?
A. Under-exposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of the clock in this image?\nA. Under-exposure\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7712,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 944:  63%|▋| 945/1495 [05:22<02:
[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 945:  63%|▋| 945/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of the clock in this image?\nA. Under-exposure\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7714,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 945:  63%|▋| 946/1495 [0
[Running Accuracy]: 0.7717,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 946:  63%|▋| 946/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Slightly blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in this image in a prominent position?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person in this image in a prominent position?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the person in this image in a prominent position?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7717,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 946:  63%|▋| 947/149
[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 947:  63%|▋| 947/1495 [05:22<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in this image in a prominent position?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of problem degrades the quality of the image?
A. Bad Exposure
B. Blurriness
C. Noises
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of problem degrades the quality of the image?
A. Bad Exposure
B. Blurriness
C. Noises
Answer with the option's letter from the given choices directly.

prompts: [["What kind of problem degrades the quality of the image?\nA. Bad Exposure\nB. Blurriness\nC. Noises\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7719,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 947:  63%|▋| 948/1495 [05:23<02:
[Running Accuracy]: 0.7711,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 948:  63%|▋| 948/1495 [05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of problem degrades the quality of the image?\nA. Bad Exposure\nB. Blurriness\nC. Noises\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7711,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 948:  63%|▋| 949/1495 [05
[Running Accuracy]: 0.7713,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 949:  63%|▋| 949/1495 [05:23<02:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have noise?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7713,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 949:  64%|▋| 950/1495 [05:23<02:4
[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 950:  64%|▋| 950/1495 [05:23<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have noise?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the donkey on the left side of the image the clearest object in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the donkey on the left side of the image the clearest object in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the donkey on the left side of the image the clearest object in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7716,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 950:  64%|▋| 951/1495 [05:24<02:
[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 951:  64%|▋| 951/1495 [05:24<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the donkey on the left side of the image the clearest object in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?
A. Coral
B. Sea anemone
C. Fish
D. Reef
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest object in the image?
A. Coral
B. Sea anemone
C. Fish
D. Reef
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest object in the image?\nA. Coral\nB. Sea anemone\nC. Fish\nD. Reef\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7718,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 951:  64%|▋| 952/1495 [05:24<02:
[Running Accuracy]: 0.7721,[Response]: C.<|endoftext|>, [Correct Ans]: Fish, , [Prog]: 952:  64%|▋| 952/1495 [05:24<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?\nA. Coral\nB. Sea anemone\nC. Fish\nD. Reef\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background mountains in this image blurred?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the background mountains in this image blurred?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the background mountains in this image blurred?\nA. Slight\nB. Moderate\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7721,[Response]: C.<|endoftext|>, [Correct Ans]: Fish, , [Prog]: 952:  64%|▋| 953/1495 [05:24<02
[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 953:  64%|▋| 953/1495 [05:24<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background mountains in this image blurred?\nA. Slight\nB. Moderate\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background of the image blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the background of the image blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the background of the image blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 953:  64%|▋| 954/1495 [05:24<
[Running Accuracy]: 0.7704,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 954:  64%|▋| 954/1495 [05:24<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background of the image blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image affected by blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image affected by blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image affected by blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7704,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 954:  64%|▋| 955/1495 [05:25<02:
[Running Accuracy]: 0.7707,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 955:  64%|▋| 955/1495 [05:25<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image affected by blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7707,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 955:  64%|▋| 956/1495 [05:25<02:
[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 956:  64%|▋| 956/1495 [05:25<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Under-exposure
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Under-exposure
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Under-exposure\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7709,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 956:  64%|▋| 957/1495 [05:25<02
[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 957:  64%|▋| 957/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Under-exposure\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?
A. Bright
B. Dim
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Bright
B. Dim
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. Bright\nB. Dim\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7712,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 957:  64%|▋| 958/1495
[Running Accuracy]: 0.7704,[Response]: C.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 958:  64%|▋| 958/1495 [05:26<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?\nA. Bright\nB. Dim\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?
A. Some blurring
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness of the image?
A. Some blurring
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness of the image?\nA. Some blurring\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7704,[Response]: C.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 958:  64%|▋| 959/1495 [05:26<02:
[Running Accuracy]: 0.7696,[Response]: B.<|endoftext|>, [Correct Ans]: Some blurring, , [Prog]: 959:  64%|▋| 959/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness of the image?\nA. Some blurring\nB. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?
A. Bunny
B. Potato
C. Cushion
D. Woodchip
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, which object is emphasized in the center?
A. Bunny
B. Potato
C. Cushion
D. Woodchip
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. Bunny\nB. Potato\nC. Cushion\nD. Woodchip\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7696,[Response]: B.<|endoftext|>, [Correct Ans]: Some blurring, , [Prog]: 959:  64%|▋| 960/1495 
[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Bunny, , [Prog]: 960:  64%|▋| 960/1495 [05:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?\nA. Bunny\nB. Potato\nC. Cushion\nD. Woodchip\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any glare in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any glare in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any glare in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Bunny, , [Prog]: 960:  64%|▋| 961/1495 [05:26<0
[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 961:  64%|▋| 961/1495 [05:26<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any glare in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color of the image?
A. Moderate
B. Monotonous
C. Rich
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color of the image?
A. Moderate
B. Monotonous
C. Rich
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color of the image?\nA. Moderate\nB. Monotonous\nC. Rich\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 961:  64%|▋| 962/1495 [05:27<02:
[Running Accuracy]: 0.7703,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 962:  64%|▋| 962/1495 [05
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color of the image?\nA. Moderate\nB. Monotonous\nC. Rich\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7703,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 962:  64%|▋| 963/1495 [05
[Running Accuracy]: 0.7695,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 963:  64%|▋| 963/1495 [05:27<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the motion blur of the ball in this image?
A. Medium
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the motion blur of the ball in this image?
A. Medium
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the motion blur of the ball in this image?\nA. Medium\nB. Strong\nC. Weak\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7695,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 963:  64%|▋| 964/1495 [05:28<
[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 964:  64%|▋| 964/1495 [05:28<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the motion blur of the ball in this image?\nA. Medium\nB. Strong\nC. Weak\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. The man
B. The girl in the red shirt
C. The building
D. The girl in the blue shirt
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. The man
B. The girl in the red shirt
C. The building
D. The girl in the blue shirt
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. The man\nB. The girl in the red shirt\nC. The building\nD. The girl in the blue shirt\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 964:  65%|▋| 965/1495 [05:28<
[Running Accuracy]: 0.7699,[Response]: D.<|endoftext|>, [Correct Ans]: The girl in the blue shirt, , [Prog]: 965:  65%
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. The man\nB. The girl in the red shirt\nC. The building\nD. The girl in the blue shirt\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers on the person's head in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the flowers on the person's head in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the flowers on the person's head in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7699,[Response]: D.<|endoftext|>, [Correct Ans]: The girl in the blue shirt, , [Prog]: 965:  65%
[Running Accuracy]: 0.7702,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 966:  65%|▋| 966/1495 [05:28<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flowers on the person's head in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7702,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 966:  65%|▋| 967/1495 [05:28<02
[Running Accuracy]: 0.7694,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 967:  65%|▋| 967/1495 [05:28<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?
A. Overexposure
B. Underexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Overexposure
B. Underexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7694,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 967:  65%|▋| 968/1495 [05:29<02
[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 968:  65%|▋| 968/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in the image?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image of the Chinese flag clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image of the Chinese flag clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image of the Chinese flag clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 968:  65%|▋| 969/1495 [
[Running Accuracy]: 0.7688,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 969:  65%|▋| 969/1495 [05:29<02:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image of the Chinese flag clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have underexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7688,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 969:  65%|▋| 970/1495 [05:30<03:1
[Running Accuracy]: 0.7680,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 970:  65%|▋| 970/1495 [05:30<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have underexposure issues?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focus in this image?
A. The man sitting in the chair
B. The woman wearing a checkered shirt
C. The man sitting on the stool
D. The girl holding a marshmallow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. The man sitting in the chair
B. The woman wearing a checkered shirt
C. The man sitting on the stool
D. The girl holding a marshmallow
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. The man sitting in the chair\nB. The woman wearing a checkered shirt\nC. The man sitting on the stool\nD. The girl holding a marshmallow\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7680,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 970:  65%|▋| 971/1495 [05:30<03:0
[Running Accuracy]: 0.7683,[Response]: D.<|endoftext|>, [Correct Ans]: The girl holding a marshmallow, , [Prog]: 971: 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focus in this image?\nA. The man sitting in the chair\nB. The woman wearing a checkered shirt\nC. The man sitting on the stool\nD. The girl holding a marshmallow\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background bright in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the background bright in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the background bright in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7683,[Response]: D.<|endoftext|>, [Correct Ans]: The girl holding a marshmallow, , [Prog]: 971: 
[Running Accuracy]: 0.7685,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 972:  65%|▋| 972/1495 [05:30<02:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background bright in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is this image blurred?
A. Strongly blurred
B. Not blurred
C. Weakly blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is this image blurred?
A. Strongly blurred
B. Not blurred
C. Weakly blurred
Answer with the option's letter from the given choices directly.

prompts: [["How severe is this image blurred?\nA. Strongly blurred\nB. Not blurred\nC. Weakly blurred\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7685,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 972:  65%|▋| 973/1495 [05:30<02:4
[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Weakly blurred, , [Prog]: 973:  65%|▋| 973/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is this image blurred?\nA. Strongly blurred\nB. Not blurred\nC. Weakly blurred\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus at the background of this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus at the background of this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus at the background of this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Weakly blurred, , [Prog]: 973:  65%|▋| 974/1495
[Running Accuracy]: 0.7680,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 974:  65%|▋| 974/1495 [05:31<03:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus at the background of this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 974:  65%|▋| 975/1495 [05:31<03:0
[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 975:  65%|▋| 975/1495 [05:31<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man holding the book emphasized in the center of the composition in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man holding the book emphasized in the center of the composition in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man holding the book emphasized in the center of the composition in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 975:  65%|▋| 976/1495 [05:32<02:
[Running Accuracy]: 0.7684,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 976:  65%|▋| 976/1495 [05:32<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the man holding the book emphasized in the center of the composition in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7684,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 976:  65%|▋| 977/1495 [05:32<02:
[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 977:  65%|▋| 977/1495 [05:32<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object of this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main object of this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main object of this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 977:  65%|▋| 978/1495 [05:32<02:
[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 978:  65%|▋| 978/1495 [05:32<02:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object of this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues exist in the image?
A. Noise
B. Motion blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues exist in the image?
A. Noise
B. Motion blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What issues exist in the image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 978:  65%|▋| 979/1495 [05:32<02:3
[Running Accuracy]: 0.7671,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 979:  65%|▋| 979/1495 [05:32<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues exist in the image?\nA. Noise\nB. Motion blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 979:  66%|▋| 980/1495 [05:33<0
[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 980:  66%|▋| 980/1495 [05:33<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any motion blur issues in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any motion blur issues in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there any motion blur issues in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 980:  66%|▋| 981/1495 [05:33<02:
[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 981:  66%|▋| 981/1495 [05:33<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any motion blur issues in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image terrifying?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image terrifying?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image terrifying?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 981:  66%|▋| 982/1495 [05:33<02:
[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 982:  66%|▋| 982/1495 [05:33<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image terrifying?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 982:  66%|▋| 983/1495 [05:34<02:
[Running Accuracy]: 0.7670,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 983:  66%|▋| 983/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pants emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pants emphasized in the center of the image composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pants emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7670,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 983:  66%|▋| 984/1495 [
[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 984:  66%|▋| 984/1495 [05:34<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pants emphasized in the center of the image composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the phorograph aesthetics of this image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the phorograph aesthetics of this image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the phorograph aesthetics of this image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 984:  66%|▋| 985/1495 [05:34<02:
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 985:  66%|▋| 985/1495 [05:34<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the phorograph aesthetics of this image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Brightness
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Brightness
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Brightness\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 985:  66%|▋| 986/1495 [05:35<03
[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 986:  66%|▋| 986/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Brightness\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Overexposure
B. Underexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Overexposure
B. Underexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 986:  66%|▋| 987/1495 [
[Running Accuracy]: 0.7680,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 987:  66%|▋| 987/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image motion-blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 987:  66%|▋| 988/1495 [
[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 988:  66%|▋| 988/1495 [05:35<02:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image motion-blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image under-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image under-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image under-exposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 988:  66%|▋| 989/1495 [05:36<03:1
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 989:  66%|▋| 989/1495 [05:36<03:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image under-exposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are penguins unrealistic in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are penguins unrealistic in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are penguins unrealistic in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 989:  66%|▋| 990/1495 [05:36<02:5
[Running Accuracy]: 0.7667,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 990:  66%|▋| 990/1495 [05:36<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are penguins unrealistic in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the trees?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the trees?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the trees?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7667,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 990:  66%|▋| 991/1495 [05:37<03:
[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 991:  66%|▋| 991/1495 [05:37<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the trees?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 991:  66%|▋| 992/1495 [05:37<03:
[Running Accuracy]: 0.7671,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 992:  66%|▋| 992/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the kumamon bear blurred in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the kumamon bear blurred in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the kumamon bear blurred in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 992:  66%|▋| 993/1495 [
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 993:  66%|▋| 993/1495 [05:37<03:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the kumamon bear blurred in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 993:  66%|▋| 994/1495 [05:38<03:1
[Running Accuracy]: 0.7676,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 994:  66%|▋| 994/1495 [05:38<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?
A. Loww
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall clarity of this image?
A. Loww
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall clarity of this image?\nA. Loww\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7676,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 994:  67%|▋| 995/1495 [05:38<03:
[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 995:  67%|▋| 995/1495 [05:38<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of this image?\nA. Loww\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this photo?
A. Keyboard
B. Monitor
C. Mouse
D. Cup
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this photo?
A. Keyboard
B. Monitor
C. Mouse
D. Cup
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this photo?\nA. Keyboard\nB. Monitor\nC. Mouse\nD. Cup\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 995:  67%|▋| 996/1495 [05:38<
[Running Accuracy]: 0.7681,[Response]: D.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 996:  67%|▋| 996/1495 [05:38<03:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this photo?\nA. Keyboard\nB. Monitor\nC. Mouse\nD. Cup\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the platform in this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the platform in this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the platform in this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7681,[Response]: D.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 996:  67%|▋| 997/1495 [05:39<02:
[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 997:  67%|▋| 997/1495 [05:39<02:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the clarity of the platform in this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this picture?
A. Advertising light boxes
B. Lanterns
C. Tables
D. People
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this picture?
A. Advertising light boxes
B. Lanterns
C. Tables
D. People
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this picture?\nA. Advertising light boxes\nB. Lanterns\nC. Tables\nD. People\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 997:  67%|▋| 998/1495 [05:39<03:
[Running Accuracy]: 0.7685,[Response]: A.<|endoftext|>, [Correct Ans]: Advertising light boxes, , [Prog]: 998:  67%|▋|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this picture?\nA. Advertising light boxes\nB. Lanterns\nC. Tables\nD. People\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7685,[Response]: A.<|endoftext|>, [Correct Ans]: Advertising light boxes, , [Prog]: 998:  67%|▋|
[Running Accuracy]: 0.7688,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 999:  67%|▋| 999/1495 [05:40<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which composition method is used in the image?
A. Symmetrical
B. Pyramidal
C. Centered
D. Diagonal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which composition method is used in the image?
A. Symmetrical
B. Pyramidal
C. Centered
D. Diagonal
Answer with the option's letter from the given choices directly.

prompts: [["Which composition method is used in the image?\nA. Symmetrical\nB. Pyramidal\nC. Centered\nD. Diagonal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7688,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 999:  67%|▋| 1000/1495 [05:40<0
[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 1000:  67%|▋| 1000/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which composition method is used in the image?\nA. Symmetrical\nB. Pyramidal\nC. Centered\nD. Diagonal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image blurred due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 1000:  67%|▋| 1001/1495 
[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1001:  67%|▋| 1001/1495 [05:40<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image blurred due to motion?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image appears the darkest?
A. Right wall
B. Left wall
C. Deer head at the top
D. Deer head at the bottom
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image appears the darkest?
A. Right wall
B. Left wall
C. Deer head at the top
D. Deer head at the bottom
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image appears the darkest?\nA. Right wall\nB. Left wall\nC. Deer head at the top\nD. Deer head at the bottom\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1001:  67%|▋| 1002/1495 [05:41<0
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Left wall, , [Prog]: 1002:  67%|▋| 1002/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image appears the darkest?\nA. Right wall\nB. Left wall\nC. Deer head at the top\nD. Deer head at the bottom\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look computer-generated or photo-realistic?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look computer-generated or photo-realistic?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look computer-generated or photo-realistic?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Left wall, , [Prog]: 1002:  67%|▋| 1003/1495 [0
[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1003:  67%|▋| 100
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look computer-generated or photo-realistic?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image feature any repeated patterns?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image feature any repeated patterns?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image feature any repeated patterns?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1003:  67%|▋| 100
[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1004:  67%|▋| 1004/1495 [05:41<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image feature any repeated patterns?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this photo?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this photo?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this photo?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1004:  67%|▋| 1005/1495 [05:41<0
[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1005:  67%|▋| 1005/1495 [05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this photo?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the sky in this image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the sky in this image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the sky in this image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1005:  67%|▋| 1006/1495 [05:4
[Running Accuracy]: 0.7674,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1006:  67%|▋| 1006/1495 [05:42<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the sky in this image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of this image?
A. Two tall buildings
B. Plants
C. The ground
D. The sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part of this image?
A. Two tall buildings
B. Plants
C. The ground
D. The sky
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part of this image?\nA. Two tall buildings\nB. Plants\nC. The ground\nD. The sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7674,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1006:  67%|▋| 1007/1495 [05:42<
[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Two tall buildings, , [Prog]: 1007:  67%|▋| 100
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of this image?\nA. Two tall buildings\nB. Plants\nC. The ground\nD. The sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sky in this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky in this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky in this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Two tall buildings, , [Prog]: 1007:  67%|▋| 100
[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1008:  67%|▋| 1008/1495 [05:42<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the sky in this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the fingers natural in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the fingers natural in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the fingers natural in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1008:  67%|▋| 1009/1495 [05:43<02
[Running Accuracy]: 0.7661,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1009:  67%|▋| 1009/1495 [05:43<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the fingers natural in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7661,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1009:  68%|▋| 1010/1495 [05:43<02
[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1010:  68%|▋| 1010/1495 [05:43<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?
A. Plain
B. Lively
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the image give?
A. Plain
B. Lively
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the image give?\nA. Plain\nB. Lively\nC. Dark\nD. Fresh\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1010:  68%|▋| 1011/1495 [05:43<
[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1011:  68%|▋| 1011/1495 [05:43<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give?\nA. Plain\nB. Lively\nC. Dark\nD. Fresh\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Would you say the composition in this image is good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Would you say the composition in this image is good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1011:  68%|▋| 1012/1495 [05:44<
[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1012:  68%|▋| 1012/1495 [05:44<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Would you say the composition in this image is good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1012:  68%|▋| 1013/1495 [05:44<0
[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1013:  68%|▋| 1013/1495 [05:44<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image pyramid-shaped?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image pyramid-shaped?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image pyramid-shaped?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1013:  68%|▋| 1014/1495 [05:44<02
[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1014:  68%|▋| 1014/1495 [05:44<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image pyramid-shaped?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the lollipops placed in the bowl in this picture vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the lollipops placed in the bowl in this picture vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the lollipops placed in the bowl in this picture vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1014:  68%|▋| 1015/1495 [05:44<02
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1015:  68%|▋| 1015/1495 [05:44<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the lollipops placed in the bowl in this picture vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1015:  68%|▋| 1016/1495 [05:45<0
[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1016:  68%|▋| 1016/1495 [05:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the sky have overexposure issues in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the sky have overexposure issues in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the sky have overexposure issues in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1016:  68%|▋| 1017/1495 [05:45<0
[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1017:  68%|▋| 1017/1495 [05:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the sky have overexposure issues in this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image centered?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image centered?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image centered?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1017:  68%|▋| 1018/1495 [05:45<0
[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1018:  68%|▋| 1018/1495 [05:45<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image centered?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the textures of the brickwall sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the textures of the brickwall sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the textures of the brickwall sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1018:  68%|▋| 1019/1495 [05:46<03
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1019:  68%|▋| 1019/1495 [05:46<03
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the textures of the brickwall sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall clarity of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall clarity of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1019:  68%|▋| 1020/1495 [05:46<03
[Running Accuracy]: 0.7676,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1020:  68%|▋| 1020/1495 [05:46<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall clarity of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Blue
B. Red
C. Green
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Blue
B. Red
C. Green
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Blue\nB. Red\nC. Green\nD. Black\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7676,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1020:  68%|▋| 1021/1495 [05:47<
[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 1021:  68%|▋| 1021/1495 [05:47<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Blue\nB. Red\nC. Green\nD. Black\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A. No

[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 1021:  68%|▋| 1022/1495 [05:47<
[Running Accuracy]: 0.7681,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 1022:  68%|▋| 1022/1495 [05:47
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A. No<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?
A. Man
B. Sofa
C. Window
D. Table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focus?
A. Man
B. Sofa
C. Window
D. Table
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focus?\nA. Man\nB. Sofa\nC. Window\nD. Table\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7681,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 1022:  68%|▋| 1023/1495 [05:47
[Running Accuracy]: 0.7683,[Response]: A.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1023:  68%|▋| 1023/1495 [05:47<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the focus?\nA. Man\nB. Sofa\nC. Window\nD. Table\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the vase?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the vase?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the vase?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7683,[Response]: A.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1023:  68%|▋| 1024/1495 [05:48<0
[Running Accuracy]: 0.7686,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1024:  68%|▋| 1024/1495 [05:48<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the vase?\nA. Poor\nB. Good\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7686,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1024:  69%|▋| 1025/1495 [05:48<
[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1025:  69%|▋| 1025/1495 [05:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color contrast of the characters in the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color contrast of the characters in the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color contrast of the characters in the image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1025:  69%|▋| 1026/1495 [05:4
[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1026:  69%|▋| 1026/1495 [05:48<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color contrast of the characters in the image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is not a main distortion in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is not a main distortion in this picture?\nA. Underexposure\nB. Motion blur\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1026:  69%|▋| 1027/1495 [05:49<
[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1027:  69%|▋| 1027/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not a main distortion in this picture?\nA. Underexposure\nB. Motion blur\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the text on the billboard in gray on the front of this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the text on the billboard in gray on the front of this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the text on the billboard in gray on the front of this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1027:  69%|▋| 1028/1495 
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1028:  69%|▋| 1028/1495 [05:49<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the text on the billboard in gray on the front of this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1028:  69%|▋| 1029/1495 [05:49<0
[Running Accuracy]: 0.7677,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1029:  69%|▋| 1029/1495 [05:49<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the clothes on the children in the image?
A. Blue
B. Black
C. Pink
D. Purple
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color scheme of the clothes on the children in the image?
A. Blue
B. Black
C. Pink
D. Purple
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color scheme of the clothes on the children in the image?\nA. Blue\nB. Black\nC. Pink\nD. Purple\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7677,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1029:  69%|▋| 1030/1495 [05:49<0
[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 1030:  69%|▋| 1030/1495 [05:49<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color scheme of the clothes on the children in the image?\nA. Blue\nB. Black\nC. Pink\nD. Purple\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have good composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have good composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have good composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 1030:  69%|▋| 1031/1495 [05:50<
[Running Accuracy]: 0.7672,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1031:  69%|▋| 1031/1495 [05:50<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have good composition?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pizza in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pizza in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pizza in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7672,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1031:  69%|▋| 1032/1495 [05:50<02
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1032:  69%|▋| 1032/1495 [05:50<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pizza in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the composition of this image use symmetry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the composition of this image use symmetry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the composition of this image use symmetry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1032:  69%|▋| 1033/1495 [05:50<02
[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1033:  69%|▋| 1033/1495 [05:50<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the composition of this image use symmetry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1033:  69%|▋| 1034/1495 [05:51<0
[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1034:  69%|▋| 1034/1495 [05:51<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Fair
B. Bad
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1034:  69%|▋| 1035/1495 [05:51<02
[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1035:  69%|▋| 1035/1495 [05:51<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Fair\nB. Bad\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1035:  69%|▋| 1036/1495 [05:51<
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1036:  69%|▋| 1036/1495 [05:51<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to movement?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?
A. White Bowl
B. Transparent Lid
C. Green Sauce
D. Bone
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, which object is emphasized in the center?
A. White Bowl
B. Transparent Lid
C. Green Sauce
D. Bone
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, which object is emphasized in the center?\nA. White Bowl\nB. Transparent Lid\nC. Green Sauce\nD. Bone\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1036:  69%|▋| 1037/1495 [05:51<0
[Running Accuracy]: 0.7676,[Response]: D.<|endoftext|>, [Correct Ans]: Bone, , [Prog]: 1037:  69%|▋| 1037/1495 [05:51<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?\nA. White Bowl\nB. Transparent Lid\nC. Green Sauce\nD. Bone\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is the image?
A. Very noisy
B. Not noisy
C. Slightly noisy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How noisy is the image?
A. Very noisy
B. Not noisy
C. Slightly noisy
Answer with the option's letter from the given choices directly.

prompts: [["How noisy is the image?\nA. Very noisy\nB. Not noisy\nC. Slightly noisy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7676,[Response]: D.<|endoftext|>, [Correct Ans]: Bone, , [Prog]: 1037:  69%|▋| 1038/1495 [05:52<
[Running Accuracy]: 0.7669,[Response]: C.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 1038:  69%|▋| 1038/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is the image?\nA. Very noisy\nB. Not noisy\nC. Slightly noisy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the horseman in the image?
A. Completely unblurry
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the horseman in the image?
A. Completely unblurry
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the horseman in the image?\nA. Completely unblurry\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7669,[Response]: C.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 1038:  69%|▋| 1039/1495 [
[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1039:  69%|▋| 1039/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the horseman in the image?\nA. Completely unblurry\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the clearest in this picture?
A. Leaf
B. Insect
C. Hole on the leaf
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the clearest in this picture?
A. Leaf
B. Insect
C. Hole on the leaf
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the clearest in this picture?\nA. Leaf\nB. Insect\nC. Hole on the leaf\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1039:  70%|▋| 1040/1
[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: Insect, , [Prog]: 1040:  70%|▋| 1040/1495 [05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the clearest in this picture?\nA. Leaf\nB. Insect\nC. Hole on the leaf\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Over-exposure
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Over-exposure
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Over-exposure\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: Insect, , [Prog]: 1040:  70%|▋| 1041/1495 [05:5
[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1041:  70%|▋| 1041/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Over-exposure\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the cloth of the subject person have rich textures?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the cloth of the subject person have rich textures?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the cloth of the subject person have rich textures?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1041:  70%|▋| 1042/14
[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1042:  70%|▋| 1042/1495 [05:53<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the cloth of the subject person have rich textures?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part in this image?
A. Ground
B. Red winterberry
C. Stone
D. Green winterberry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part in this image?
A. Ground
B. Red winterberry
C. Stone
D. Green winterberry
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part in this image?\nA. Ground\nB. Red winterberry\nC. Stone\nD. Green winterberry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1042:  70%|▋| 1043/1495 [05:53<0
[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Red winterberry, , [Prog]: 1043:  70%|▋| 1043/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part in this image?\nA. Ground\nB. Red winterberry\nC. Stone\nD. Green winterberry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Normal
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Normal
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Normal\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Red winterberry, , [Prog]: 1043:  70%|▋| 1044/1
[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1044:  70%|▋| 1044/1495 [05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Normal\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of photographic technique is used?
A. Black and White
B. Symmetrical Composition
C. Shallow Depth-of-Field
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of photographic technique is used?
A. Black and White
B. Symmetrical Composition
C. Shallow Depth-of-Field
Answer with the option's letter from the given choices directly.

prompts: [["What kind of photographic technique is used?\nA. Black and White\nB. Symmetrical Composition\nC. Shallow Depth-of-Field\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1044:  70%|▋| 1045/1495 [05:5
[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Shallow Depth-of-Field, , [Prog]: 1045:  70%|▋|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of photographic technique is used?\nA. Black and White\nB. Symmetrical Composition\nC. Shallow Depth-of-Field\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the package in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the package in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the package in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Shallow Depth-of-Field, , [Prog]: 1045:  70%|▋|
[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1046:  70%|▋| 1046/1495 [05:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the package in this image vibrant?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?
A. Photo-realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic or computer-generated?
A. Photo-realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic or computer-generated?\nA. Photo-realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1046:  70%|▋| 1047/1495 [05:54<0
[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1047:  70%|▋| 1047/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?\nA. Photo-realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?
A. Plane
B. People
C. Roof
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Plane
B. People
C. Roof
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Plane\nB. People\nC. Roof\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1047:  70%|▋| 1048/1
[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: Plane, , [Prog]: 1048:  70%|▋| 1048/1495 [05:55
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?\nA. Plane\nB. People\nC. Roof\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color in the image?
A. Rich
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color in the image?
A. Rich
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color in the image?\nA. Rich\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: Plane, , [Prog]: 1048:  70%|▋| 1049/1495 [05:55
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Rich, , [Prog]: 1049:  70%|▋| 1049/1495 [05:55<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How rich is the color in the image?\nA. Rich\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most blurry part in this image?
A. Trees
B. The object held in the hand
C. Backpack
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most blurry part in this image?
A. Trees
B. The object held in the hand
C. Backpack
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["What is the most blurry part in this image?\nA. Trees\nB. The object held in the hand\nC. Backpack\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Rich, , [Prog]: 1049:  70%|▋| 1050/1495 [05:55<
[Running Accuracy]: 0.7667,[Response]: B.<|endoftext|>, [Correct Ans]: The object held in the hand, , [Prog]: 1050:  7
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most blurry part in this image?\nA. Trees\nB. The object held in the hand\nC. Backpack\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7667,[Response]: B.<|endoftext|>, [Correct Ans]: The object held in the hand, , [Prog]: 1050:  7
[Running Accuracy]: 0.7659,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1051:  70%|▋| 1051/1495 [05:56<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the hat people are wearing in this image?
A. Moderate
B. Bright
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the hat people are wearing in this image?
A. Moderate
B. Bright
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the hat people are wearing in this image?\nA. Moderate\nB. Bright\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7659,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1051:  70%|▋| 1052/1495 [05:56<02
[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1052:  70%|▋| 1052/1495 [05:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the hat people are wearing in this image?\nA. Moderate\nB. Bright\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, is the beer mug emphasized in the center?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, is the beer mug emphasized in the center?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, is the beer mug emphasized in the center?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1052:  70%|▋| 1053/1495 [05:5
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1053:  70%|▋| 1053/1495 [05:56<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, is the beer mug emphasized in the center?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1053:  71%|▋| 1054/1495 [05:57<0
[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1054:  71%|▋| 1054/1495 [05:57<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?
A. Cardboard
B. Surfboard
C. Door
D. Wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition of the image, which object is emphasized in the center?
A. Cardboard
B. Surfboard
C. Door
D. Wall
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of the image, which object is emphasized in the center?\nA. Cardboard\nB. Surfboard\nC. Door\nD. Wall\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1054:  71%|▋| 1055/1495 [05:57<0
[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Surfboard, , [Prog]: 1055:  71%|▋| 1055/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In the composition of the image, which object is emphasized in the center?\nA. Cardboard\nB. Surfboard\nC. Door\nD. Wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion exists in the image?
A. Backlighting
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion exists in the image?
A. Backlighting
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What distortion exists in the image?\nA. Backlighting\nB. Motion blur\nC. Overexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Surfboard, , [Prog]: 1055:  71%|▋| 1056/1495 [0
[Running Accuracy]: 0.7670,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1056:  71%|▋| 1056/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion exists in the image?\nA. Backlighting\nB. Motion blur\nC. Overexposure\nD. Compression artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7670,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1056:  71%|▋| 1057/1495
[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1057:  71%|▋| 1057/1495 [05:58<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of degradation is clearly visible in the image?
A. Underexposure
B. Blur
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of degradation is clearly visible in the image?
A. Underexposure
B. Blur
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of degradation is clearly visible in the image?\nA. Underexposure\nB. Blur\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1057:  71%|▋| 1058/1495 [05:58<
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1058:  71%|▋| 1058/1495 [05:58<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of degradation is clearly visible in the image?\nA. Underexposure\nB. Blur\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1058:  71%|▋| 1059/1495 [05:58<
[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1059:  71%|▋| 1059/1495 [05:58<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the frog emphasized in the center in image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the frog emphasized in the center in image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the frog emphasized in the center in image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1059:  71%|▋| 1060/1495 [05:59<0
[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1060:  71%|▋| 1060/1495 [05:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the frog emphasized in the center in image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image saturated?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image saturated?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1060:  71%|▋| 1061/1495 [05:59<0
[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1061:  71%|▋| 1061/1495 [05:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?
A. The woods
B. The jet
C. The sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of this image?
A. The woods
B. The jet
C. The sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. The woods\nB. The jet\nC. The sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1061:  71%|▋| 1062/1495 [05:59<0
[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: The jet, , [Prog]: 1062:  71%|▋| 1062/1495 [05:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?\nA. The woods\nB. The jet\nC. The sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?
A. Yellow
B. Blue
C. Pink
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the image?
A. Yellow
B. Blue
C. Pink
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Yellow\nB. Blue\nC. Pink\nD. Black\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: The jet, , [Prog]: 1062:  71%|▋| 1063/1495 [05:
[Running Accuracy]: 0.7667,[Response]: C.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 1063:  71%|▋| 1063/1495 [05:59<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the image?\nA. Yellow\nB. Blue\nC. Pink\nD. Black\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are all robots in focus, or part of the robots in focus, or none of them in focus?
A. Part
B. All
C. None
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are all robots in focus, or part of the robots in focus, or none of them in focus?
A. Part
B. All
C. None
Answer with the option's letter from the given choices directly.

prompts: [["Are all robots in focus, or part of the robots in focus, or none of them in focus?\nA. Part\nB. All\nC. None\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7667,[Response]: C.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 1063:  71%|▋| 1064/1495 [06:00<
[Running Accuracy]: 0.7669,[Response]: A.<|endoftext|>, [Correct Ans]: Part, , [Prog]: 1064:  71%|▋| 1064/1495 [06:00<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are all robots in focus, or part of the robots in focus, or none of them in focus?\nA. Part\nB. All\nC. None\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give people?
A. Fresh
B. Happy
C. Dark
D. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the image give people?
A. Fresh
B. Happy
C. Dark
D. Bright
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the image give people?\nA. Fresh\nB. Happy\nC. Dark\nD. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7669,[Response]: A.<|endoftext|>, [Correct Ans]: Part, , [Prog]: 1064:  71%|▋| 1065/1495 [06:00<
[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1065:  71%|▋| 1065/1495 [06:00<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual perception does the image give people?\nA. Fresh\nB. Happy\nC. Dark\nD. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the predominant distortion in this image?
A. Noise
B. Compression
C. Blur
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the predominant distortion in this image?
A. Noise
B. Compression
C. Blur
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the predominant distortion in this image?\nA. Noise\nB. Compression\nC. Blur\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1065:  71%|▋| 1066/1495 [06:00<
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1066:  71%|▋| 1066/1495 [06:00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the predominant distortion in this image?\nA. Noise\nB. Compression\nC. Blur\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a refreshing visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing visual impression?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1066:  71%|▋| 1067/1495 [06:01
[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1067:  71%|▋| 1067/1495 [06:01<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual impression?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1067:  71%|▋| 1068/1495 [06:01<02
[Running Accuracy]: 0.7669,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1068:  71%|▋| 1068/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. High\nB. Low\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Motion blur
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Motion blur
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Motion blur\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7669,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1068:  72%|▋| 1069/1495 [
[Running Accuracy]: 0.7671,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1069:  72%|▋| 1069/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Motion blur\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7671,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1069:  72%|▋| 1070/149
[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1070:  72%|▋| 1070/1495 [06:02<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the lighting condition of the image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the lighting condition of the image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What is the lighting condition of the image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7673,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1070:  72%|▋| 1071/1495 [06:02<02
[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1071:  72%|▋| 1071/1495 [06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the lighting condition of the image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part of this image?
A. Electric bike
B. Vegetation
C. Ground
D. Buildings
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part of this image?
A. Electric bike
B. Vegetation
C. Ground
D. Buildings
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part of this image?\nA. Electric bike\nB. Vegetation\nC. Ground\nD. Buildings\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7675,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1071:  72%|▋| 1072/1495 [06:0
[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Electric bike, , [Prog]: 1072:  72%|▋| 1072/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest part of this image?\nA. Electric bike\nB. Vegetation\nC. Ground\nD. Buildings\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Low
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Low
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Low\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Electric bike, , [Prog]: 1072:  72%|▋| 1073/149
[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1073:  72%|▋| 1073/1495 [06:03<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Low\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of motion blur does this image have?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of motion blur does this image have?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of motion blur does this image have?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1073:  72%|▋| 1074/1495 [06:03<
[Running Accuracy]: 0.7672,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1074:  72%|▋| 1074/1495 [06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of motion blur does this image have?\nA. Slight\nB. Severe\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual perception?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a dark visual perception?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark visual perception?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7672,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1074:  72%|▋| 1075/1495 [06:0
[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1075:  72%|▋| 1075/1495 [06:04<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual perception?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does this image suffer from?
A. Blur
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does this image suffer from?
A. Blur
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does this image suffer from?\nA. Blur\nB. Noise\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7674,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1075:  72%|▋| 1076/1495 [06:04<0
[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1076:  72%|▋| 1076/1495 [06:04
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does this image suffer from?\nA. Blur\nB. Noise\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in the image a man?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main object in the image a man?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main object in the image a man?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1076:  72%|▋| 1077/1495 [06:04
[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1077:  72%|▋| 1077/1495 [06:04<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main object in the image a man?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?
A. Electric bike
B. Dead tree
C. Flower pond
D. Pavilion
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is emphasized in the center?
A. Electric bike
B. Dead tree
C. Flower pond
D. Pavilion
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is emphasized in the center?\nA. Electric bike\nB. Dead tree\nC. Flower pond\nD. Pavilion\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1077:  72%|▋| 1078/1495 [06:05<0
[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: Dead tree, , [Prog]: 1078:  72%|▋| 1078/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is emphasized in the center?\nA. Electric bike\nB. Dead tree\nC. Flower pond\nD. Pavilion\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: Dead tree, , [Prog]: 1078:  72%|▋| 1079/1495 [0
[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1079:  72%|▋| 1079/1495 [06:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the stickers in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the stickers in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the stickers in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1079:  72%|▋| 1080/1495 [06:05<
[Running Accuracy]: 0.7685,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1080:  72%|▋| 1080/1495 [06:05<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the stickers in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?
A. Trees
B. People and horses
C. Stable
D. Fence
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, which object is emphasized in the center?
A. Trees
B. People and horses
C. Stable
D. Fence
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. Trees\nB. People and horses\nC. Stable\nD. Fence\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7685,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1080:  72%|▋| 1081/1495 [06:06<
[Running Accuracy]: 0.7687,[Response]: B.<|endoftext|>, [Correct Ans]: People and horses, , [Prog]: 1081:  72%|▋| 1081
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?\nA. Trees\nB. People and horses\nC. Stable\nD. Fence\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Fair
B. Dim
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Fair
B. Dim
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Fair\nB. Dim\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7687,[Response]: B.<|endoftext|>, [Correct Ans]: People and horses, , [Prog]: 1081:  72%|▋| 1082
[Running Accuracy]: 0.7689,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1082:  72%|▋| 1082/1495 [06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Fair\nB. Dim\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically good?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7689,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1082:  72%|▋| 1083/1495 [06:0
[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1083:  72%|▋| 1083/1495 [06:07<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically good?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the human in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the human in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the human in the center of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1083:  73%|▋| 1084/1495 [06:07<02
[Running Accuracy]: 0.7694,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1084:  73%|▋| 1084/1495 [06:07<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the human in the center of this picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stump in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the stump in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the stump in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7694,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1084:  73%|▋| 1085/1495 [06:07<0
[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1085:  73%|▋| 1085/1495 [06:07<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the stump in this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color rich in the image?
A. Average
B. Rich
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color rich in the image?
A. Average
B. Rich
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["Is the color rich in the image?\nA. Average\nB. Rich\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1085:  73%|▋| 1086/1495 [06:08<0
[Running Accuracy]: 0.7689,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1086:  73%|▋| 1086/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color rich in the image?\nA. Average\nB. Rich\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a sense of visual enjoyment?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a sense of visual enjoyment?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a sense of visual enjoyment?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7689,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1086:  73%|▋| 1087/1495 [
[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1087:  73%|▋| 1087/1495 [06:08<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a sense of visual enjoyment?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle clear in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vehicle clear in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the vehicle clear in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1087:  73%|▋| 1088/1495 [06:08<02
[Running Accuracy]: 0.7684,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1088:  73%|▋| 1088/1495 [06:08<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle clear in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7684,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1088:  73%|▋| 1089/1495 [06:09<02
[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1089:  73%|▋| 1089/1495 [06:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pelican in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pelican in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pelican in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1089:  73%|▋| 1090/1495 [06:0
[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1090:  73%|▋| 1090/1495 [06:09<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the pelican in the image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image of the cows in high image quality?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image of the cows in high image quality?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["Is the image of the cows in high image quality?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7679,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1090:  73%|▋| 1091/1495 [06:09<0
[Running Accuracy]: 0.7681,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1091:  73%|▋| 1091/1495 [06:09<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image of the cows in high image quality?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image's sharpness?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image's sharpness?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the image's sharpness?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7681,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1091:  73%|▋| 1092/1495 [06:09<0
[Running Accuracy]: 0.7674,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1092:  73%|▋| 1092/1495 [06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image's sharpness?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?
A. Gloomy
B. Sunny
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Gloomy
B. Sunny
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Gloomy\nB. Sunny\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7674,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1092:  73%|▋| 1093/1495 [06:
[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Sunny, , [Prog]: 1093:  73%|▋| 1093/1495 [06:10
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the image?\nA. Gloomy\nB. Sunny\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7676,[Response]: B.<|endoftext|>, [Correct Ans]: Sunny, , [Prog]: 1093:  73%|▋| 1094/1495 [06:10
[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1094:  73%|▋| 1094/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion does this image mainly suffer?
A. Noise
B. Compression
C. Blurriness
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion does this image mainly suffer?
A. Noise
B. Compression
C. Blurriness
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion does this image mainly suffer?\nA. Noise\nB. Compression\nC. Blurriness\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1094:  73%|▋| 1095/1495 [
[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 1095:  73%|▋| 1095/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion does this image mainly suffer?\nA. Noise\nB. Compression\nC. Blurriness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest part of this image?
A. Tree
B. Sky
C. Pedestrian
D. Building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the darkest part of this image?
A. Tree
B. Sky
C. Pedestrian
D. Building
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest part of this image?\nA. Tree\nB. Sky\nC. Pedestrian\nD. Building\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7680,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 1095:  73%|▋| 1096/1495 [
[Running Accuracy]: 0.7673,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1096:  73%|▋| 1096/1495 [06:11<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the darkest part of this image?\nA. Tree\nB. Sky\nC. Pedestrian\nD. Building\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7673,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1096:  73%|▋| 1097/1495 [06:11<0
[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1097:  73%|▋| 1097/1495 [06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1097:  73%|▋| 1098/1495 [06:1
[Running Accuracy]: 0.7659,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1098:  73%|▋| 1098/1495 [06:12<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7659,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1098:  74%|▋| 1099/1495 [06:12<
[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1099:  74%|▋| 1099/1495 [06:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1099:  74%|▋| 1100/1495 [06:12<0
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1100:  74%|▋| 1100/1495 [06:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Big tree
B. Building
C. Street light
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Big tree
B. Building
C. Street light
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Big tree\nB. Building\nC. Street light\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1100:  74%|▋| 1101/1495 [06:13<0
[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Street light, , [Prog]: 1101:  74%|▋| 1101/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Big tree\nB. Building\nC. Street light\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the focus of this image?
A. The background wall
B. The girl
C. The food on the table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the focus of this image?
A. The background wall
B. The girl
C. The food on the table
Answer with the option's letter from the given choices directly.

prompts: [["What is the focus of this image?\nA. The background wall\nB. The girl\nC. The food on the table\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: Street light, , [Prog]: 1101:  74%|▋| 1102/1495
[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: The girl, , [Prog]: 1102:  74%|▋| 1102/1495 [06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the focus of this image?\nA. The background wall\nB. The girl\nC. The food on the table\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the food on the table in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the food on the table in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the food on the table in this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: The girl, , [Prog]: 1102:  74%|▋| 1103/1495 [06
[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1103:  74%|▋| 1103/1495 [06:13<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the food on the table in this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is being emphasized in the center?
A. Girl wearing black top
B. Girl with backpack
C. Building
D. Boy wearing black top
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the composition of this image is being emphasized in the center?
A. Girl wearing black top
B. Girl with backpack
C. Building
D. Boy wearing black top
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the composition of this image is being emphasized in the center?\nA. Girl wearing black top\nB. Girl with backpack\nC. Building\nD. Boy wearing black top\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1103:  74%|▋| 1104/1495 [06:14<0
[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Girl with backpack, , [Prog]: 1104:  74%|▋| 110
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the composition of this image is being emphasized in the center?\nA. Girl wearing black top\nB. Girl with backpack\nC. Building\nD. Boy wearing black top\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?
A. Yellow
B. Green
C. White
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone in the image?
A. Yellow
B. Green
C. White
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone in the image?\nA. Yellow\nB. Green\nC. White\nD. Red\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Girl with backpack, , [Prog]: 1104:  74%|▋| 110
[Running Accuracy]: 0.7665,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1105:  74%|▋| 1105/1495 [06:14<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone in the image?\nA. Yellow\nB. Green\nC. White\nD. Red\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from above?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the light in this image come from above?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the light in this image come from above?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7665,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1105:  74%|▋| 1106/1495 [06:14<0
[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1106:  74%|▋| 1106/1495 [06:14<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the light in this image come from above?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the cat in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the cat in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the cat in this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1106:  74%|▋| 1107/1495 [06:15<0
[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1107:  74%|▋| 1107/1495 [06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the cat in this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness in the image's subject?
A. Slightly blurry
B. Completely sharp
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness in the image's subject?
A. Slightly blurry
B. Completely sharp
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness in the image's subject?\nA. Slightly blurry\nB. Completely sharp\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7669,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1107:  74%|▋| 1108/1495 [06:1
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1108:  74%|▋| 1108/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the degree of blurriness in the image's subject?\nA. Slightly blurry\nB. Completely sharp\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1108:  74%|▋| 1109/1
[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1109:  74%|▋| 1109/1495 [06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image central?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image central?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image central?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1109:  74%|▋| 1110/1495 [06:1
[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1110:  74%|▋| 1110/1495 [06:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image central?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?
A. Lawn
B. Dog
C. Pillar
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Lawn
B. Dog
C. Pillar
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Lawn\nB. Dog\nC. Pillar\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1110:  74%|▋| 1111/1495 [06:16<0
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 1111:  74%|▋| 1111/1495 [06:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?\nA. Lawn\nB. Dog\nC. Pillar\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Moderate\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 1111:  74%|▋| 1112/1495 [06:17<0
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1112:  74%|▋| 1112/1495 [06:17
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the image?\nA. Moderate\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the primary subject distinguishable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the primary subject distinguishable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the primary subject distinguishable?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1112:  74%|▋| 1113/1495 [06:17
[Running Accuracy]: 0.7664,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1113:  74%|▋| 1113/1495 [06:17<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the primary subject distinguishable?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image?
A. potted plant
B. cabinet
C. man
D. lamp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the image?
A. potted plant
B. cabinet
C. man
D. lamp
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the image?\nA. potted plant\nB. cabinet\nC. man\nD. lamp\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7664,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1113:  75%|▋| 1114/1495 [06:17<0
[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: man, , [Prog]: 1114:  75%|▋| 1114/1495 [06:17<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of the image?\nA. potted plant\nB. cabinet\nC. man\nD. lamp\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall color saturation of the image like?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall color saturation of the image like?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall color saturation of the image like?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7666,[Response]: C.<|endoftext|>, [Correct Ans]: man, , [Prog]: 1114:  75%|▋| 1115/1495 [06:18<0
[Running Accuracy]: 0.7668,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1115:  75%|▋| 1115/1495 [06:18<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall color saturation of the image like?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Dark
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7668,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1115:  75%|▋| 1116/1495 [06:18<0
[Running Accuracy]: 0.7670,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1116:  75%|▋| 1116/1495 [06:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Dark\nB. Bright\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?
A. Over-exposure
B. Medium
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of this image?
A. Over-exposure
B. Medium
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of this image?\nA. Over-exposure\nB. Medium\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7670,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1116:  75%|▋| 1117/1495 [06:1
[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1117:  75%|▋| 1117/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?\nA. Over-exposure\nB. Medium\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color contrast of this image strong?
A. Weak
B. Moderate
C. Strong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color contrast of this image strong?
A. Weak
B. Moderate
C. Strong
Answer with the option's letter from the given choices directly.

prompts: [["Is the color contrast of this image strong?\nA. Weak\nB. Moderate\nC. Strong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1117:  75%|▋| 1118/149
[Running Accuracy]: 0.7665,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1118:  75%|▋| 1118/1495 [06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color contrast of this image strong?\nA. Weak\nB. Moderate\nC. Strong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7665,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1118:  75%|▋| 1119/1495 [06
[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1119:  75%|▋| 1119/1495 [06:19<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the red lantern in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the red lantern in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the red lantern in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1119:  75%|▋| 1120/1495 [06:20<
[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1120:  75%|▋| 1120/1495 [06:20<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the red lantern in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1120:  75%|▋| 1121/1495 [06:20<0
[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1121:  75%|▋| 1121/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the exposure level in the image?
A. Underexposed
B. Moderate
C. Overexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the exposure level in the image?
A. Underexposed
B. Moderate
C. Overexposed
Answer with the option's letter from the given choices directly.

prompts: [["What is the exposure level in the image?\nA. Underexposed\nB. Moderate\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1121:  75%|▊| 1122/1495
[Running Accuracy]: 0.7656,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1122:  75%|▊| 1122/1495 [06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the exposure level in the image?\nA. Underexposed\nB. Moderate\nC. Overexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the colors of the letters H and M in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the colors of the letters H and M in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the colors of the letters H and M in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7656,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1122:  75%|▊| 1123/1495 [06
[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1123:  75%|▊| 1123/1495 [06:21<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the colors of the letters H and M in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1123:  75%|▊| 1124/1495 [06:22<0
[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1124:  75%|▊| 1124/1495 [06:22<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1124:  75%|▊| 1125/1495 [06:22<02
[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1125:  75%|▊| 1125/1495 [06:22<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1125:  75%|▊| 1126/1495 [06:23<02
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1126:  75%|▊| 1126/1495 [06:23<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image seem unfocused?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image seem unfocused?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1126:  75%|▊| 1127/1495 [06:23<0
[Running Accuracy]: 0.7657,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1127:  75%|▊| 1127/1495 [06:23<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image in a pyramid style?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image in a pyramid style?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image in a pyramid style?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7657,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1127:  75%|▊| 1128/1495 [06:23<0
[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1128:  75%|▊| 1128/1495 [06:23<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image in a pyramid style?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image has the darkest color?
A. Roof
B. Text on the wall
C. Photo album on the wall
D. Cup on the wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image has the darkest color?
A. Roof
B. Text on the wall
C. Photo album on the wall
D. Cup on the wall
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image has the darkest color?\nA. Roof\nB. Text on the wall\nC. Photo album on the wall\nD. Cup on the wall\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1128:  76%|▊| 1129/1495 [06:24<02
[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: Roof, , [Prog]: 1129:  76%|▊| 1129/1495 [06:24<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of this image has the darkest color?\nA. Roof\nB. Text on the wall\nC. Photo album on the wall\nD. Cup on the wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Good\nB. Acceptable\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: Roof, , [Prog]: 1129:  76%|▊| 1130/1495 [06:24<
[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1130:  76%|▊| 1130/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?\nA. Good\nB. Acceptable\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where does the light in this picture come from?
A. From below
B. From above
C. From the side
D. From behind
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where does the light in this picture come from?
A. From below
B. From above
C. From the side
D. From behind
Answer with the option's letter from the given choices directly.

prompts: [["Where does the light in this picture come from?\nA. From below\nB. From above\nC. From the side\nD. From behind\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1130:  76%|▊| 1131/1495 [
[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: From below, , [Prog]: 1131:  76%|▊| 1131/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where does the light in this picture come from?\nA. From below\nB. From above\nC. From the side\nD. From behind\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: From below, , [Prog]: 1131:  76%|▊| 1132/1495 [
[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1132:  76%|▊| 1132/1495 [06:25<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background sky blurred in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the background sky blurred in this image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the background sky blurred in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1132:  76%|▊| 1133/1495 [06:26<
[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1133:  76%|▊| 1133/1495 [06:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background sky blurred in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Good
B. Fair
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Good
B. Fair
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Good\nB. Fair\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1133:  76%|▊| 1134/1495 [06:2
[Running Accuracy]: 0.7637,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1134:  76%|▊| 1134/1495 [06:26<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Good\nB. Fair\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any compression artifats on the singer's face?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any compression artifats on the singer's face?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there any compression artifats on the singer's face?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7637,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1134:  76%|▊| 1135/1495 [06:27<
[Running Accuracy]: 0.7630,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1135:  76%|▊| 1135/1495 [06:27<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there any compression artifats on the singer's face?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness exists in this image of the warning sign?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blurriness exists in this image of the warning sign?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blurriness exists in this image of the warning sign?\nA. Slight\nB. Moderate\nC. Severe\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7630,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1135:  76%|▊| 1136/1495 [06:27<0
[Running Accuracy]: 0.7623,[Response]: C.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1136:  76%|▊| 1136/1495 [06:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degree of blurriness exists in this image of the warning sign?\nA. Slight\nB. Moderate\nC. Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest part of this image?
A. Buildings
B. Pork
C. Fish
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest part of this image?
A. Buildings
B. Pork
C. Fish
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest part of this image?\nA. Buildings\nB. Pork\nC. Fish\nD. Ground\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7623,[Response]: C.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1136:  76%|▊| 1137/1495 [06:2
[Running Accuracy]: 0.7625,[Response]: B.<|endoftext|>, [Correct Ans]: Pork, , [Prog]: 1137:  76%|▊| 1137/1495 [06:27<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest part of this image?\nA. Buildings\nB. Pork\nC. Fish\nD. Ground\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7625,[Response]: B.<|endoftext|>, [Correct Ans]: Pork, , [Prog]: 1137:  76%|▊| 1138/1495 [06:28<
[Running Accuracy]: 0.7627,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1138:  76%|▊| 1138/1495 [06:28<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Overexposure
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Overexposure
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Overexposure\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7627,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1138:  76%|▊| 1139/1495 [06:28<0
[Running Accuracy]: 0.7629,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1139:  76%|▊| 1139/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Overexposure\nB. Motion blur\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flowers on the roof in this image?
A. Medium
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the flowers on the roof in this image?
A. Medium
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the flowers on the roof in this image?\nA. Medium\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7629,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1139:  76%|▊| 1140/1495
[Running Accuracy]: 0.7623,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1140:  76%|▊| 1140/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flowers on the roof in this image?\nA. Medium\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is in the center of this picture?
A. Grass
B. Pond
C. Bears
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is in the center of this picture?
A. Grass
B. Pond
C. Bears
Answer with the option's letter from the given choices directly.

prompts: [["What is in the center of this picture?\nA. Grass\nB. Pond\nC. Bears\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7623,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1140:  76%|▊| 1141/1495 [
[Running Accuracy]: 0.7625,[Response]: C.<|endoftext|>, [Correct Ans]: Bears, , [Prog]: 1141:  76%|▊| 1141/1495 [06:29
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is in the center of this picture?\nA. Grass\nB. Pond\nC. Bears\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall brightness of the image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall brightness of the image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7625,[Response]: C.<|endoftext|>, [Correct Ans]: Bears, , [Prog]: 1141:  76%|▊| 1142/1495 [06:30
[Running Accuracy]: 0.7627,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1142:  76%|▊| 1142/1495 [06:30<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall brightness of the image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality problems does not exist in this image?
A. Underexposure
B. Out-of-focus
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality problems does not exist in this image?
A. Underexposure
B. Out-of-focus
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality problems does not exist in this image?\nA. Underexposure\nB. Out-of-focus\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7627,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1142:  76%|▊| 1143/1495 [06:30<
[Running Accuracy]: 0.7629,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1143:  76%|▊| 1143/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality problems does not exist in this image?\nA. Underexposure\nB. Out-of-focus\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little mouse in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little mouse in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the little mouse in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7629,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1143:  77%|▊| 1144/1495
[Running Accuracy]: 0.7631,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1144:  77%|▊| 1144/1495 [06:30<02
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little mouse in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus at the front of the picture or at the back?
A. Back
B. Front
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus at the front of the picture or at the back?
A. Back
B. Front
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus at the front of the picture or at the back?\nA. Back\nB. Front\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7631,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1144:  77%|▊| 1145/1495 [06:31<02
[Running Accuracy]: 0.7633,[Response]: B.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 1145:  77%|▊| 1145/1495 [06:31
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus at the front of the picture or at the back?\nA. Back\nB. Front\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the image?
A. Overexposed
B. Just fine
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of the image?
A. Overexposed
B. Just fine
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of the image?\nA. Overexposed\nB. Just fine\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7633,[Response]: B.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 1145:  77%|▊| 1146/1495 [06:31
[Running Accuracy]: 0.7635,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 1146:  77%|▊| 1146/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the image?\nA. Overexposed\nB. Just fine\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion for the background on the top left?
A. Over-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion for the background on the top left?
A. Over-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion for the background on the top left?\nA. Over-exposure\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7635,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 1146:  77%|▊| 1147/1495 [0
[Running Accuracy]: 0.7637,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1147:  77%|▊| 1147/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion for the background on the top left?\nA. Over-exposure\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7637,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1147:  77%|▊| 1148/149
[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1148:  77%|▊| 1148/1495 [06:32
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Brightness
B. Noise
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Brightness
B. Noise
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Brightness\nB. Noise\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1148:  77%|▊| 1149/1495 [06:32
[Running Accuracy]: 0.7641,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1149:  77%|▊| 1149/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Brightness\nB. Noise\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the noise level of this image?
A. Acceptable
B. Weak
C. Srong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the noise level of this image?
A. Acceptable
B. Weak
C. Srong
Answer with the option's letter from the given choices directly.

prompts: [["What is the noise level of this image?\nA. Acceptable\nB. Weak\nC. Srong\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7641,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1149:  77%|▊| 1150/1495
[Running Accuracy]: 0.7643,[Response]: C.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 1150:  77%|▊| 1150/1495 [06:33
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the noise level of this image?\nA. Acceptable\nB. Weak\nC. Srong\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does this image not have?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does this image not have?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7643,[Response]: C.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 1150:  77%|▊| 1151/1495 [06:33
[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1151:  77%|▊| 1151/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the figure in the image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the figure in the image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the figure in the image?\nA. Clear\nB. Blurry\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1151:  77%|▊| 1152/149
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1152:  77%|▊| 1152/1495 [06:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the figure in the image?\nA. Clear\nB. Blurry\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the fur of the tiger blurred?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the fur of the tiger blurred?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the fur of the tiger blurred?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1152:  77%|▊| 1153/1495 [06:3
[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1153:  77%|▊| 1153/1495 [06:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the fur of the tiger blurred?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1153:  77%|▊| 1154/1495 [06:34<0
[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1154:  77%|▊| 1154/1495 [06:34<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have motion blur?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the subject in this image?
A. Red
B. Yellow
C. White
D. Green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the subject in this image?
A. Red
B. Yellow
C. White
D. Green
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the subject in this image?\nA. Red\nB. Yellow\nC. White\nD. Green\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1154:  77%|▊| 1155/1495 [06:34<01
[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1155:  77%|▊| 1155/1495 [06:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color tone of the subject in this image?\nA. Red\nB. Yellow\nC. White\nD. Green\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation high in this image?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation high in this image?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation high in this image?\nA. High\nB. Low\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1155:  77%|▊| 1156/1495 [06:35<0
[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1156:  77%|▊| 1156/1495 [06:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation high in this image?\nA. High\nB. Low\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the image?
A. Average
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1156:  77%|▊| 1157/1495 [06:35<
[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1157:  77%|▊| 1157/1495 [06:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?\nA. Average\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion happens in this image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion happens in this image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion happens in this image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1157:  77%|▊| 1158/1495 [06:35<
[Running Accuracy]: 0.7660,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1158:  77%|▊| 1158/1495 [06:35
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion happens in this image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual feeling does the style of the image give?
A. dark
B. terrifying
C. fresh
D. passionate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feeling does the style of the image give?
A. dark
B. terrifying
C. fresh
D. passionate
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feeling does the style of the image give?\nA. dark\nB. terrifying\nC. fresh\nD. passionate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1158:  78%|▊| 1159/1495 [06:36
[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: passionate, , [Prog]: 1159:  78%|▊| 1159/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual feeling does the style of the image give?\nA. dark\nB. terrifying\nC. fresh\nD. passionate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From the composition perspective, what is the main object in this picture?
A. Trees
B. Road
C. Streetlights
D. People
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From the composition perspective, what is the main object in this picture?
A. Trees
B. Road
C. Streetlights
D. People
Answer with the option's letter from the given choices directly.

prompts: [["From the composition perspective, what is the main object in this picture?\nA. Trees\nB. Road\nC. Streetlights\nD. People\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7653,[Response]: C.<|endoftext|>, [Correct Ans]: passionate, , [Prog]: 1159:  78%|▊| 1160/1495 [
[Running Accuracy]: 0.7655,[Response]: D.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1160:  78%|▊| 1160/1495 [06:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From the composition perspective, what is the main object in this picture?\nA. Trees\nB. Road\nC. Streetlights\nD. People\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?
A. Grass
B. Alarm clock
C. Yellow flower
D. Stone table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Grass
B. Alarm clock
C. Yellow flower
D. Stone table
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Grass\nB. Alarm clock\nC. Yellow flower\nD. Stone table\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7655,[Response]: D.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1160:  78%|▊| 1161/1495 [06:3
[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Alarm clock, , [Prog]: 1161:  78%|▊| 1161/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?\nA. Grass\nB. Alarm clock\nC. Yellow flower\nD. Stone table\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters on the signs in this picture?
A. Blurry
B. Clear
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters on the signs in this picture?
A. Blurry
B. Clear
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters on the signs in this picture?\nA. Blurry\nB. Clear\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Alarm clock, , [Prog]: 1161:  78%|▊| 1162/1495 
[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1162:  78%|▊| 1162/1495 [06:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters on the signs in this picture?\nA. Blurry\nB. Clear\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1162:  78%|▊| 1163/1495 [06:3
[Running Accuracy]: 0.7653,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1163:  78%|▊| 1163/1495 [06:38<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the image?\nA. Poor\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7653,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1163:  78%|▊| 1164/1495 [06:38<0
[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1164:  78%|▊| 1164/1495 [06:38<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the image?\nA. Poor\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe distortionin this image?
A. Out of focus
B. Motion Blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe distortionin this image?
A. Out of focus
B. Motion Blur
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe distortionin this image?\nA. Out of focus\nB. Motion Blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1164:  78%|▊| 1165/1495 [06:38<
[Running Accuracy]: 0.7648,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1165:  78%|▊| 1165/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most severe distortionin this image?\nA. Out of focus\nB. Motion Blur\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1165:  78%|▊| 1166/149
[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1166:  78%|▊| 1166/1495 [06:39<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have overexposure issues?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the front of the yellow car in this image blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the front of the yellow car in this image blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the front of the yellow car in this image blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1166:  78%|▊| 1167/1495 [06:39<01
[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1167:  78%|▊| 1167/1495 [06:39<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the front of the yellow car in this image blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1167:  78%|▊| 1168/1495 [06:39<01
[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1168:  78%|▊| 1168/1495 [06:39<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there recurring patterns in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there recurring patterns in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1168:  78%|▊| 1169/1495 [06:40<0
[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1169:  78%|▊| 1169/1495 [06:40<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there recurring patterns in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Clear
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1169:  78%|▊| 1170/1495 [06:40<0
[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1170:  78%|▊| 1170/1495 [06:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Blurry\nB. Clear\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1170:  78%|▊| 1171/1495 [06:4
[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1171:  78%|▊| 1171/1495 [06:40<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise problem in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the signposts in this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the signposts in this image?
A. Noise
B. Over-exposure
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the signposts in this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1171:  78%|▊| 1172/1495 [06:40<0
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1172:  78%|▊| 1172/1495 [06:41<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the signposts in this image?\nA. Noise\nB. Over-exposure\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the background of the image look dark?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the background of the image look dark?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the background of the image look dark?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1172:  78%|▊| 1173/1495 [06:41<
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1173:  78%|▊| 1173/1495 [06:41<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the background of the image look dark?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1173:  79%|▊| 1174/1495 [06:41<0
[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1174:  79%|▊| 1174/1495 [06:41<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Noise
B. Motion blur
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Noise
B. Motion blur
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7666,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1174:  79%|▊| 1175/1495 [06:41<01
[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1175:  79%|▊| 1175/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there excessive noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there excessive noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there excessive noise in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7668,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1175:  79%|▊| 1176/1495 
[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1176:  79%|▊| 1176/1495 [06:42<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there excessive noise in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1176:  79%|▊| 1177/1495 [06:42<01
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1177:  79%|▊| 1177/1495 [06:42<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flowers in this image?
A. Moderate
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the flowers in this image?
A. Moderate
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the flowers in this image?\nA. Moderate\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1177:  79%|▊| 1178/1495 [06:42<0
[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1178:  79%|▊| 1178/1495 [06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flowers in this image?\nA. Moderate\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the soccer field in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the soccer field in the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the soccer field in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1178:  79%|▊| 1179/1495 [06:
[Running Accuracy]: 0.7651,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1179:  79%|▊| 1179/1495 [06:43<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the soccer field in the image?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7651,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1179:  79%|▊| 1180/1495 [06:43<
[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1180:  79%|▊| 1180/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does not exist in this image?
A. Overexposure
B. Blur
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does not exist in this image?
A. Overexposure
B. Blur
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does not exist in this image?\nA. Overexposure\nB. Blur\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1180:  79%|▊| 1181/1495
[Running Accuracy]: 0.7655,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1181:  79%|▊| 1181/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does not exist in this image?\nA. Overexposure\nB. Blur\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?
A. Normal
B. Bright
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Normal
B. Bright
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Normal\nB. Bright\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7655,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1181:  79%|▊| 1182/149
[Running Accuracy]: 0.7657,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1182:  79%|▊| 1182/1495 [06:44<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is this picture?\nA. Normal\nB. Bright\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is the night sky in this image?
A. Slightly noisy
B. Very noisy
C. Not noisy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How noisy is the night sky in this image?
A. Slightly noisy
B. Very noisy
C. Not noisy
Answer with the option's letter from the given choices directly.

prompts: [["How noisy is the night sky in this image?\nA. Slightly noisy\nB. Very noisy\nC. Not noisy\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7657,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1182:  79%|▊| 1183/1495 [06:45<
[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 1183:  79%|▊| 1183/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How noisy is the night sky in this image?\nA. Slightly noisy\nB. Very noisy\nC. Not noisy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of  in this image?
A. Over-exposure
B. Low light
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of  in this image?
A. Over-exposure
B. Low light
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of  in this image?\nA. Over-exposure\nB. Low light\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 1183:  79%|▊| 1184/1495 [
[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: Low light, , [Prog]: 1184:  79%|▊| 1184/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of  in this image?\nA. Over-exposure\nB. Low light\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: Low light, , [Prog]: 1184:  79%|▊| 1185/1495 [0
[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1185:  79%|▊| 1185/1495 [06:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image saturated?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of the image overall?
A. Church
B. Fallen leaves
C. Tree trunk
D. Tombstone
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part of the image overall?
A. Church
B. Fallen leaves
C. Tree trunk
D. Tombstone
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part of the image overall?\nA. Church\nB. Fallen leaves\nC. Tree trunk\nD. Tombstone\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1185:  79%|▊| 1186/1495 [06:46<0
[Running Accuracy]: 0.7648,[Response]: D.<|endoftext|>, [Correct Ans]: Fallen leaves, , [Prog]: 1186:  79%|▊| 1186/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of the image overall?\nA. Church\nB. Fallen leaves\nC. Tree trunk\nD. Tombstone\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issue does this image not have?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issue does this image not have?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issue does this image not have?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7648,[Response]: D.<|endoftext|>, [Correct Ans]: Fallen leaves, , [Prog]: 1186:  79%|▊| 1187/149
[Running Accuracy]: 0.7641,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1187:  79%|▊| 1187/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issue does this image not have?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the exposure level of the traffic sign in the image?
A. Moderate
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the exposure level of the traffic sign in the image?
A. Moderate
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["What is the exposure level of the traffic sign in the image?\nA. Moderate\nB. Overexposed\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7641,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1187:  79%|▊| 1188/1495
[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1188:  79%|▊| 1188/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the exposure level of the traffic sign in the image?\nA. Moderate\nB. Overexposed\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity of this picture?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity of this picture?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity of this picture?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1188:  80%|▊| 1189/1495
[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1189:  80%|▊| 1189/1495 [06:47<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity of this picture?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?
A. Compression artifacts
B. Motion blur
C. Backlighting
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in this image?
A. Compression artifacts
B. Motion blur
C. Backlighting
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in this image?\nA. Compression artifacts\nB. Motion blur\nC. Backlighting\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1189:  80%|▊| 1190/1495 [06:47<0
[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 1190:  80%|▊| 1190/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problems exist in this image?\nA. Compression artifacts\nB. Motion blur\nC. Backlighting\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the content in the image generated by AI?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the content in the image generated by AI?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the content in the image generated by AI?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 1190:  80%|▊| 1191/1495
[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1191:  80%|▊| 1191/1495 [06:47<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the content in the image generated by AI?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the car in this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the car in this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the car in this image colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1191:  80%|▊| 1192/1495 [06:48<0
[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1192:  80%|▊| 1192/1495 [06:48<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the car in this image colorful?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1192:  80%|▊| 1193/1495 [06:48<01
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1193:  80%|▊| 1193/1495 [06:48<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little girl clear in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little girl clear in the picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the little girl clear in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1193:  80%|▊| 1194/1495 [06:48<01
[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1194:  80%|▊| 1194/1495 [06:48<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little girl clear in the picture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1194:  80%|▊| 1195/1495 [06:49<0
[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1195:  80%|▊| 1195/1495 [06:49<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flower in this image?
A. Vibrant
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the flower in this image?
A. Vibrant
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the flower in this image?\nA. Vibrant\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1195:  80%|▊| 1196/1495 [06:49<0
[Running Accuracy]: 0.7651,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1196:  80%|▊| 1196/1495 [06:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the flower in this image?\nA. Vibrant\nB. Monotonous\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is most severely affected by overexposure?
A. Building
B. Characters
C. Streetlight
D. Sword
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is most severely affected by overexposure?
A. Building
B. Characters
C. Streetlight
D. Sword
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is most severely affected by overexposure?\nA. Building\nB. Characters\nC. Streetlight\nD. Sword\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7651,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1196:  80%|▊| 1197/1495 [06:
[Running Accuracy]: 0.7644,[Response]: C.<|endoftext|>, [Correct Ans]: Sword, , [Prog]: 1197:  80%|▊| 1197/1495 [06:49
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is most severely affected by overexposure?\nA. Building\nB. Characters\nC. Streetlight\nD. Sword\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Very blurry
B. Not blurry at all
C. Somewhat blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Very blurry
B. Not blurry at all
C. Somewhat blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Very blurry\nB. Not blurry at all\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7644,[Response]: C.<|endoftext|>, [Correct Ans]: Sword, , [Prog]: 1197:  80%|▊| 1198/1495 [06:50
[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1198:  80%|▊| 1198/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Very blurry\nB. Not blurry at all\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dog emphasized in the center of this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dog emphasized in the center of this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog emphasized in the center of this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1198:  80%|▊| 1199/1495 
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1199:  80%|▊| 1199/1495 [06:50<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the dog emphasized in the center of this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light in the image come?
A. Bottom side
B. Right side
C. Top side
D. Left side
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light in the image come?
A. Bottom side
B. Right side
C. Top side
D. Left side
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light in the image come?\nA. Bottom side\nB. Right side\nC. Top side\nD. Left side\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1199:  80%|▊| 1200/1495 [06:51<0
[Running Accuracy]: 0.7642,[Response]: A.<|endoftext|>, [Correct Ans]: Right side, , [Prog]: 1200:  80%|▊| 1200/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light in the image come?\nA. Bottom side\nB. Right side\nC. Top side\nD. Left side\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7642,[Response]: A.<|endoftext|>, [Correct Ans]: Right side, , [Prog]: 1200:  80%|▊| 1201/1495 [
[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1201:  80%|▊| 1201/1495 [06:51<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Good\nB. Poor\nC. Fair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this picture?
A. Wall
B. Rocks
C. Pots
D. Plants
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of this picture?
A. Wall
B. Rocks
C. Pots
D. Plants
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this picture?\nA. Wall\nB. Rocks\nC. Pots\nD. Plants\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1201:  80%|▊| 1202/1495 [06:51<
[Running Accuracy]: 0.7646,[Response]: D.<|endoftext|>, [Correct Ans]: Plants, , [Prog]: 1202:  80%|▊| 1202/1495 [06:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the center of this picture?\nA. Wall\nB. Rocks\nC. Pots\nD. Plants\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion of this picture?
A. Out of focus
B. Noise
C. Overexposure
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion of this picture?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: D.<|endoftext|>, [Correct Ans]: Plants, , [Prog]: 1202:  80%|▊| 1203/1495 [06:5
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1203:  80%|▊| 1203/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?\nA. Out of focus\nB. Noise\nC. Overexposure\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color pleasing in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color pleasing in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color pleasing in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1203:  81%|▊| 1204/1495
[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1204:  81%|▊| 1204/1495 [06:52<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color pleasing in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the brightest in this picture?
A. Trees
B. Bench
C. Child
D. Buildings
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the brightest in this picture?
A. Trees
B. Bench
C. Child
D. Buildings
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the brightest in this picture?\nA. Trees\nB. Bench\nC. Child\nD. Buildings\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1204:  81%|▊| 1205/1495 [06:53<02
[Running Accuracy]: 0.7643,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 1205:  81%|▊| 1205/1495 [06:53
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the brightest in this picture?\nA. Trees\nB. Bench\nC. Child\nD. Buildings\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7643,[Response]: C.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 1205:  81%|▊| 1206/1495 [06:54
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1206:  81%|▊| 1206/1495 [06:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture dark?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1206:  81%|▊| 1207/1495 [06:54<0
[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1207:  81%|▊| 1207/1495 [06:54<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Over-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Over-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Over-exposure\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1207:  81%|▊| 1208/1495 [06:54<0
[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1208:  81%|▊| 1208/1495 [06:54<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Over-exposure\nB. Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?
A. Lawn
B. Tree
C. Flowerbed
D. Cat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Lawn
B. Tree
C. Flowerbed
D. Cat
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Lawn\nB. Tree\nC. Flowerbed\nD. Cat\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1208:  81%|▊| 1209/1495 [06:55<
[Running Accuracy]: 0.7651,[Response]: D.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 1209:  81%|▊| 1209/1495 [06:55<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?\nA. Lawn\nB. Tree\nC. Flowerbed\nD. Cat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the bottle in this image?
A. Blur
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion of the bottle in this image?
A. Blur
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of the bottle in this image?\nA. Blur\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7651,[Response]: D.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 1209:  81%|▊| 1210/1495 [06:55<0
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1210:  81%|▊| 1210/1495 [06:55<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion of the bottle in this image?\nA. Blur\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography style is used in this image?
A. Background Bokeh
B. Motion Blur
C. Black and White
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What photography style is used in this image?
A. Background Bokeh
B. Motion Blur
C. Black and White
Answer with the option's letter from the given choices directly.

prompts: [["What photography style is used in this image?\nA. Background Bokeh\nB. Motion Blur\nC. Black and White\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1210:  81%|▊| 1211/1495 [06:55<
[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Background Bokeh, , [Prog]: 1211:  81%|▊| 1211/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography style is used in this image?\nA. Background Bokeh\nB. Motion Blur\nC. Black and White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image faded?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image faded?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image faded?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Background Bokeh, , [Prog]: 1211:  81%|▊| 1212/
[Running Accuracy]: 0.7640,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1212:  81%|▊| 1212/1495 [06:56<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image faded?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the subject in the image?
A. Moderate
B. Blurry
C. Sharp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the subject in the image?
A. Moderate
B. Blurry
C. Sharp
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the subject in the image?\nA. Moderate\nB. Blurry\nC. Sharp\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7640,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1212:  81%|▊| 1213/1495 [06:56<0
[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Sharp, , [Prog]: 1213:  81%|▊| 1213/1495 [06:56
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the subject in the image?\nA. Moderate\nB. Blurry\nC. Sharp\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Sharp, , [Prog]: 1213:  81%|▊| 1214/1495 [06:56
[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1214:  81%|▊| 1214/1495 [06:56
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the fur on the fox's head in the image?
A. Blurry
B. Average
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the fur on the fox's head in the image?
A. Blurry
B. Average
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the fur on the fox's head in the image?\nA. Blurry\nB. Average\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1214:  81%|▊| 1215/1495 [06:57
[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1215:  81%|▊| 1215/1495 [06:57
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the fur on the fox's head in the image?\nA. Blurry\nB. Average\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overal clarity of this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overal clarity of this image?
A. High
B. Acceptable
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What is the overal clarity of this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1215:  81%|▊| 1216/1495 [06:57
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1216:  81%|▊| 1216/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overal clarity of this image?\nA. High\nB. Acceptable\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the leaves suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the leaves suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the leaves suffer from over-exposure?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1216:  81%|▊| 1217/1495 [
[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1217:  81%|▊| 1217/1495 [06:58<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Do the leaves suffer from over-exposure?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the visibility of the large characters in this image?
A. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the visibility of the large characters in this image?
A. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the visibility of the large characters in this image?\nA. Bad\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1217:  81%|▊| 1218/1495 [06:58<0
[Running Accuracy]: 0.7652,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1218:  81%|▊| 1218/1495 [06:58<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the visibility of the large characters in this image?\nA. Bad\nB. Fair\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the camera clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the camera clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the camera clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1218:  82%|▊| 1219/1495 [06:59<
[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1219:  82%|▊| 1219/1495 [06:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the camera clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How are the colors in this picture?
A. Fair
B. Dull
C. Vivid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How are the colors in this picture?
A. Fair
B. Dull
C. Vivid
Answer with the option's letter from the given choices directly.

prompts: [["How are the colors in this picture?\nA. Fair\nB. Dull\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1219:  82%|▊| 1220/1495 [06:59<0
[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1220:  82%|▊| 1220/1495 [06:59<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How are the colors in this picture?\nA. Fair\nB. Dull\nC. Vivid\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Noise
B. Overexposure
C. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Noise
B. Overexposure
C. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Noise\nB. Overexposure\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1220:  82%|▊| 1221/1495 [07:00<
[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1221:  82%|▊| 1221/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Noise\nB. Overexposure\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bench clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bench clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the bench clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1221:  82%|▊| 1222/1495
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1222:  82%|▊| 1222/1495 [07:00<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the bench clear in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1222:  82%|▊| 1223/1495 [07:00<01
[Running Accuracy]: 0.7661,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1223:  82%|▊| 1223/1495 [07:00<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is wheat emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is wheat emphasized in the center of the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is wheat emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1223:  82%|▊| 1224/1495 [07:01<0
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1224:  82%|▊| 1224/1495 [07:01<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is wheat emphasized in the center of the image composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Good
B. Fair
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Good
B. Fair
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Good\nB. Fair\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1224:  82%|▊| 1225/1495 [07:01<0
[Running Accuracy]: 0.7657,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1225:  82%|▊| 1225/1495 [07:01<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Good\nB. Fair\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issue does this image not have?
A. Out of focus
B. Underexposure
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issue does this image not have?
A. Out of focus
B. Underexposure
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What quality issue does this image not have?\nA. Out of focus\nB. Underexposure\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7657,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1225:  82%|▊| 1226/1495 [07:01<
[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1226:  82%|▊| 1226/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issue does this image not have?\nA. Out of focus\nB. Underexposure\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this photo?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this photo?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this photo?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1226:  82%|▊| 1227/1495
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1227:  82%|▊| 1227/1495 [07:02<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this photo?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image overexposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image overexposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image overexposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1227:  82%|▊| 1228/1495 [07:02<
[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1228:  82%|▊| 1228/1495 [07:02<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image overexposed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1228:  82%|▊| 1229/1495 [07:02<0
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1229:  82%|▊| 1229/1495 [07:02<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this picture good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this picture good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this picture good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1229:  82%|▊| 1230/1495 [07:03<0
[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1230:  82%|▊| 1230/1495 [07:03<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this picture good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image use a shallow depth of field effect?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image use a shallow depth of field effect?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image use a shallow depth of field effect?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1230:  82%|▊| 1231/1495 [07:03<01
[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1231:  82%|▊| 1231/1495 [07:03<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image use a shallow depth of field effect?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the upper part of the image the brightest?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the upper part of the image the brightest?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the upper part of the image the brightest?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1231:  82%|▊| 1232/1495 [07:03<0
[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1232:  82%|▊| 1232/1495 [07:03<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the upper part of the image the brightest?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the grass and ground rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the grass and ground rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the grass and ground rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1232:  82%|▊| 1233/1495 [07:04<0
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1233:  82%|▊| 1233/1495 [07:04<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the grass and ground rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the black-topped person on the left clear in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the black-topped person on the left clear in this photo?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the black-topped person on the left clear in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1233:  83%|▊| 1234/1495 [07:04<0
[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1234:  83%|▊| 1234/1495 [07:04<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the black-topped person on the left clear in this photo?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1234:  83%|▊| 1235/1495 [07:05<01
[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1235:  83%|▊| 1235/1495 [07:05<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Is this image photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7652,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1235:  83%|▊| 1236/1495 [07:05<01
[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1236:  83%|▊| 1236/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1236:  83%|▊| 1237/1
[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1237:  83%|▊| 1237/1495 [07:05<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?
A. Average
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Average
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Average\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1237:  83%|▊| 1238/1495 [07:05<01
[Running Accuracy]: 0.7649,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1238:  83%|▊| 1238/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the image?\nA. Average\nB. Bad\nC. Excellent\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7649,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1238:  83%|▊| 1239/1495 [07:
[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1239:  83%|▊| 1239/1495 [07:06<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the picture?
A. Over-exposure
B. Under-exposure
C. Appropriate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of the picture?
A. Over-exposure
B. Under-exposure
C. Appropriate
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of the picture?\nA. Over-exposure\nB. Under-exposure\nC. Appropriate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1239:  83%|▊| 1240/1495 [07:06<01
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1240:  83%|▊| 1240/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the picture?\nA. Over-exposure\nB. Under-exposure\nC. Appropriate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1240:  83%|▊| 1241/14
[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1241:  83%|▊| 1241/1495 [07:07<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image rich in color?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1241:  83%|▊| 1242/1495 [07:07<0
[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1242:  83%|▊| 1242/1495 [07:07<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image rich in color?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image have?
A. Overexposure
B. Underexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does this image have?
A. Overexposure
B. Underexposure
C. Out of focus
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does this image have?\nA. Overexposure\nB. Underexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1242:  83%|▊| 1243/1495 [07:07<0
[Running Accuracy]: 0.7643,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1243:  83%|▊| 1243/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does this image have?\nA. Overexposure\nB. Underexposure\nC. Out of focus\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7643,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1243:  83%|▊| 1244/149
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1244:  83%|▊| 1244/1495 [07:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the owl in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the owl in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the owl in the picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1244:  83%|▊| 1245/1495 [07:08<
[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1245:  83%|▊| 1245/1495 [07:08<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the owl in the picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual sensation does this image give?
A. Dull
B. Gloomy
C. Vibrant
D. Restless
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual sensation does this image give?
A. Dull
B. Gloomy
C. Vibrant
D. Restless
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual sensation does this image give?\nA. Dull\nB. Gloomy\nC. Vibrant\nD. Restless\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1245:  83%|▊| 1246/1495 [07:08<0
[Running Accuracy]: 0.7648,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1246:  83%|▊| 1246/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual sensation does this image give?\nA. Dull\nB. Gloomy\nC. Vibrant\nD. Restless\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which level of blur can be noticed in this image?
A. Strong Blur
B. Weak Blur
C. No Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which level of blur can be noticed in this image?
A. Strong Blur
B. Weak Blur
C. No Blur
Answer with the option's letter from the given choices directly.

prompts: [["Which level of blur can be noticed in this image?\nA. Strong Blur\nB. Weak Blur\nC. No Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7648,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1246:  83%|▊| 1247/1495 [07:
[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Weak Blur, , [Prog]: 1247:  83%|▊| 1247/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which level of blur can be noticed in this image?\nA. Strong Blur\nB. Weak Blur\nC. No Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Somewhat blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Weak Blur, , [Prog]: 1247:  83%|▊| 1248/1495 [0
[Running Accuracy]: 0.7644,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1248:  83%|▊| 1248
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Somewhat blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7644,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1248:  84%|▊| 1249
[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1249:  84%|▊| 1249/1495 [07:10<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1249:  84%|▊| 1250/1495 [07:10<
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1250:  84%|▊| 1250/1495 [07:10<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture have noise?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does this image not have?
A. Underexposure
B. Noise
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality issue does this image not have?
A. Underexposure
B. Noise
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue does this image not have?\nA. Underexposure\nB. Noise\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1250:  84%|▊| 1251/1495 [07:11<0
[Running Accuracy]: 0.7642,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1251:  84%|▊| 1251/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does this image not have?\nA. Underexposure\nB. Noise\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Was shallow depth of field used in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Was shallow depth of field used in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Was shallow depth of field used in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7642,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1251:  84%|▊| 1252/149
[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1252:  84%|▊| 1252/1495 [07:11<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Was shallow depth of field used in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image very clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image very clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image very clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1252:  84%|▊| 1253/1495 [07:11<01
[Running Accuracy]: 0.7630,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1253:  84%|▊| 1253/1495 [07:11<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image very clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the image?
A. Totally Black and White
B. Very Vibrant
C. Slightly Faded
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the image?
A. Totally Black and White
B. Very Vibrant
C. Slightly Faded
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the image?\nA. Totally Black and White\nB. Very Vibrant\nC. Slightly Faded\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7630,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1253:  84%|▊| 1254/1495 [07:12<0
[Running Accuracy]: 0.7632,[Response]: A.<|endoftext|>, [Correct Ans]: Totally Black and White, , [Prog]: 1254:  84%|▊
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the image?\nA. Totally Black and White\nB. Very Vibrant\nC. Slightly Faded\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the blur level of the image?
A. Slightly blurred
B. Extremely blurred
C. Not blurred at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the blur level of the image?
A. Slightly blurred
B. Extremely blurred
C. Not blurred at all
Answer with the option's letter from the given choices directly.

prompts: [["What is the blur level of the image?\nA. Slightly blurred\nB. Extremely blurred\nC. Not blurred at all\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7632,[Response]: A.<|endoftext|>, [Correct Ans]: Totally Black and White, , [Prog]: 1254:  84%|▊
[Running Accuracy]: 0.7633,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurred, , [Prog]: 1255:  84%|▊| 1255/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the blur level of the image?\nA. Slightly blurred\nB. Extremely blurred\nC. Not blurred at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7633,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurred, , [Prog]: 1255:  84%|▊| 1256/
[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1256:  84%|▊| 1256/1495 [07:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the composition of this image symmetrical?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Bad
B. Medium
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1256:  84%|▊| 1257/1495 [07:13<0
[Running Accuracy]: 0.7637,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1257:  84%|▊| 1257/1495 [07:13<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition in this image?\nA. Bad\nB. Medium\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a refreshing visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7637,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1257:  84%|▊| 1258/1495 [07:13<
[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1258:  84%|▊| 1258/1495 [07:13<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a refreshing visual impression?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?
A. Railing
B. Woman
C. Grass
D. Man
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of this image?
A. Railing
B. Woman
C. Grass
D. Man
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. Railing\nB. Woman\nC. Grass\nD. Man\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1258:  84%|▊| 1259/1495 [07:13<0
[Running Accuracy]: 0.7641,[Response]: D.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1259:  84%|▊| 1259/1495 [07:13<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of this image?\nA. Railing\nB. Woman\nC. Grass\nD. Man\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an overexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there an overexposure problem in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there an overexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7641,[Response]: D.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1259:  84%|▊| 1260/1495 [07:13<0
[Running Accuracy]: 0.7643,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1260:  84%|▊| 1260/1495 [07:13<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there an overexposure problem in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is present in this image?
A. Overexposure
B. Motion Blur
C. Noise
D. Out of Focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion is present in this image?
A. Overexposure
B. Motion Blur
C. Noise
D. Out of Focus
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion is present in this image?\nA. Overexposure\nB. Motion Blur\nC. Noise\nD. Out of Focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7643,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1260:  84%|▊| 1261/1495 [07:14<01
[Running Accuracy]: 0.7645,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1261:  84%|▊| 1261/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is present in this image?\nA. Overexposure\nB. Motion Blur\nC. Noise\nD. Out of Focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image seem unfocused?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1261:  84%|▊| 1262/1495
[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1262:  84%|▊| 1262/1495 [07:14<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image seem unfocused?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In this image composition, is the lizard emphasized in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In this image composition, is the lizard emphasized in the center?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["In this image composition, is the lizard emphasized in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1262:  84%|▊| 1263/1495 [07:15<0
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1263:  84%|▊| 1263/1495 [07:15<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In this image composition, is the lizard emphasized in the center?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Clear
B. Fair
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Fair
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Fair\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1263:  85%|▊| 1264/1495 [07:15<0
[Running Accuracy]: 0.7650,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1264:  85%|▊| 1264/1495 [07:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Clear\nB. Fair\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have glare?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have glare?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have glare?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7650,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1264:  85%|▊| 1265/1495 [07:1
[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1265:  85%|▊| 1265/1495 [07:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have glare?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness exists in the bullfighter in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blurriness exists in the bullfighter in this image?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness exists in the bullfighter in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1265:  85%|▊| 1266/1495 [07:16<0
[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1266:  85%|▊| 1266/1495 [07:1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What level of blurriness exists in the bullfighter in this image?\nA. Severe\nB. Slight\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there excessive noise and chromatic aberrations in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there excessive noise and chromatic aberrations in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there excessive noise and chromatic aberrations in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1266:  85%|▊| 1267/1495 [07:1
[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1267:  85%|▊| 1267/1495 [07:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are there excessive noise and chromatic aberrations in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image saturation?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image saturation?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the image saturation?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7656,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1267:  85%|▊| 1268/1495 [07:16<0
[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1268:  85%|▊| 1268/1495 [07:16<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image saturation?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues does the image have?
A. Overexposure
B. Motion blur
C. Underexposure
D. Compression distortion
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issues does the image have?
A. Overexposure
B. Motion blur
C. Underexposure
D. Compression distortion
Answer with the option's letter from the given choices directly.

prompts: [["What quality issues does the image have?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Compression distortion\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1268:  85%|▊| 1269/1495 [07:17<
[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Compression distortion, , [Prog]: 1269:  85%|▊|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues does the image have?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Compression distortion\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the picture is clearer?
A. The center
B. The surrounding areas
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the picture is clearer?
A. The center
B. The surrounding areas
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the picture is clearer?\nA. The center\nB. The surrounding areas\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: Compression distortion, , [Prog]: 1269:  85%|▊|
[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: The center, , [Prog]: 1270:  85%|▊| 1270/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the picture is clearer?\nA. The center\nB. The surrounding areas\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the arrangement of elements in this image?
A. Good
B. Bad
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the arrangement of elements in this image?
A. Good
B. Bad
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the arrangement of elements in this image?\nA. Good\nB. Bad\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7654,[Response]: A.<|endoftext|>, [Correct Ans]: The center, , [Prog]: 1270:  85%|▊| 1271/1495 [
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1271:  85%|▊| 1271/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the arrangement of elements in this image?\nA. Good\nB. Bad\nC. Acceptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color tone of the ground in this image?
A. Reddish
B. Grayish
C. Blueish
D. Greenish
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color tone of the ground in this image?
A. Reddish
B. Grayish
C. Blueish
D. Greenish
Answer with the option's letter from the given choices directly.

prompts: [["What is the color tone of the ground in this image?\nA. Reddish\nB. Grayish\nC. Blueish\nD. Greenish\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1271:  85%|▊| 1272/1495 [
[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Reddish, , [Prog]: 1272:  85%|▊| 1272/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color tone of the ground in this image?\nA. Reddish\nB. Grayish\nC. Blueish\nD. Greenish\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the yellow duck in this image?
A. Vivid
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the yellow duck in this image?
A. Vivid
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the yellow duck in this image?\nA. Vivid\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Reddish, , [Prog]: 1272:  85%|▊| 1273/1495 [07:
[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Vivid, , [Prog]: 1273:  85%|▊| 1273/1495 [07:18
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the yellow duck in this image?\nA. Vivid\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the brightest part of the image in the center of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the brightest part of the image in the center of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the brightest part of the image in the center of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Vivid, , [Prog]: 1273:  85%|▊| 1274/1495 [07:19
[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1274:  85%|▊| 1274/1495 [07:19<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the brightest part of the image in the center of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman facing away from the frame in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman facing away from the frame in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman facing away from the frame in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7645,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1274:  85%|▊| 1275/1495 [07:19<0
[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1275:  85%|▊| 1275/1495 [07:19<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman facing away from the frame in focus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the shrub in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the shrub in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the shrub in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1275:  85%|▊| 1276/1495 [07:19<01
[Running Accuracy]: 0.7633,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1276:  85%|▊| 1276/1495 [07:19<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the shrub in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?
A. Blur
B. Low contrast
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of this image?
A. Blur
B. Low contrast
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of this image?\nA. Blur\nB. Low contrast\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7633,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1276:  85%|▊| 1277/1495 [07:20<01
[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1277:  85%|▊| 1277/1495 [07:20<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most apparent distortion of this image?\nA. Blur\nB. Low contrast\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a gloomy feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a gloomy feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a gloomy feeling?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1277:  85%|▊| 1278/1495 [07:20<
[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1278:  85%|▊| 1278/1495 [07:20<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a gloomy feeling?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the blueberry emphasized in the center in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the blueberry emphasized in the center in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the blueberry emphasized in the center in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1278:  86%|▊| 1279/1495 [07:20<0
[Running Accuracy]: 0.7639,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1279:  86%|▊| 1279/1495 [07:20<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the blueberry emphasized in the center in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part is the brightest in this image?
A. Spoon
B. Chestnut
C. Container
D. Lamp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part is the brightest in this image?
A. Spoon
B. Chestnut
C. Container
D. Lamp
Answer with the option's letter from the given choices directly.

prompts: [["Which part is the brightest in this image?\nA. Spoon\nB. Chestnut\nC. Container\nD. Lamp\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7639,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1279:  86%|▊| 1280/1495 [07:21<0
[Running Accuracy]: 0.7633,[Response]: D.<|endoftext|>, [Correct Ans]: Chestnut, , [Prog]: 1280:  86%|▊| 1280/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part is the brightest in this image?\nA. Spoon\nB. Chestnut\nC. Container\nD. Lamp\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall lighting of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7633,[Response]: D.<|endoftext|>, [Correct Ans]: Chestnut, , [Prog]: 1280:  86%|▊| 1281/1495 [07
[Running Accuracy]: 0.7627,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1281:  86%|▊| 1281/1495 [07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall lighting of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?
A. Noise
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does this image not have?
A. Noise
B. Underexposure
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does this image not have?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7627,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1281:  86%|▊| 1282/1495 [07:2
[Running Accuracy]: 0.7629,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1282:  86%|▊| 1282/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does this image not have?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of the image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of the image?
A. Fair
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of the image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7629,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1282:  86%|▊| 1283/149
[Running Accuracy]: 0.7623,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1283:  86%|▊| 1283/1495 [07:22<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the composition of the image?\nA. Fair\nB. Good\nC. Bad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two antelopes in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two antelopes in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the two antelopes in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7623,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1283:  86%|▊| 1284/1495 [07:22<
[Running Accuracy]: 0.7625,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1284:  86%|▊| 1284/1495 [07:22<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two antelopes in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the trees in the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the trees in the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the trees in the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7625,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1284:  86%|▊| 1285/1495 [07:23<0
[Running Accuracy]: 0.7626,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1285:  86%|▊| 1285/1495 [07:23<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the trees in the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7626,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1285:  86%|▊| 1286/1495 [07:23<
[Running Accuracy]: 0.7628,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1286:  86%|▊| 1286/1495 [07:23<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the image's background?
A. Very bright
B. Very dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the image's background?
A. Very bright
B. Very dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the image's background?\nA. Very bright\nB. Very dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7628,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1286:  86%|▊| 1287/1495 [07:23<0
[Running Accuracy]: 0.7630,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1287:  86%|▊| 1287/1495 [07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of the image's background?\nA. Very bright\nB. Very dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image looks brightest?
A. The trees in the background
B. The car on the right side of the frame
C. The car on the left side of the frame
D. The clouds in the sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image looks brightest?
A. The trees in the background
B. The car on the right side of the frame
C. The car on the left side of the frame
D. The clouds in the sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image looks brightest?\nA. The trees in the background\nB. The car on the right side of the frame\nC. The car on the left side of the frame\nD. The clouds in the sky\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7630,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1287:  86%|▊| 1288/1495 [07:2
[Running Accuracy]: 0.7632,[Response]: C.<|endoftext|>, [Correct Ans]: The car on the left side of the frame, , [Prog]
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object in the image looks brightest?\nA. The trees in the background\nB. The car on the right side of the frame\nC. The car on the left side of the frame\nD. The clouds in the sky\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the handlebar of the bicycle clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the handlebar of the bicycle clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the handlebar of the bicycle clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7632,[Response]: C.<|endoftext|>, [Correct Ans]: The car on the left side of the frame, , [Prog]
[Running Accuracy]: 0.7634,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1289:  86%|▊| 1289/1495 [07:24<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the handlebar of the bicycle clear in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image well-composed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image well-composed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7634,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1289:  86%|▊| 1290/1495 [07:24<0
[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1290:  86%|▊| 1290/1495 [07:24<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image well-composed?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of this image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of this image full?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of this image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1290:  86%|▊| 1291/1495 [07:25<01
[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1291:  86%|▊| 1291/1495 [07:25<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of this image full?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1291:  86%|▊| 1292/1495 [07:25<0
[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1292:  86%|▊| 1292/1495 [07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How would you rate the lighting of this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus of this picture?
A. Center
B. Background
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Center
B. Background
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Center\nB. Background\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1292:  86%|▊| 1293/1495 [07:2
[Running Accuracy]: 0.7633,[Response]: B.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 1293:  86%|▊| 1293/1495 [07:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Where is the focus of this picture?\nA. Center\nB. Background\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What main distortion can be seen on the bear in this image?
A. Blur
B. Noise
C. Overexposure
D. Compression Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What main distortion can be seen on the bear in this image?
A. Blur
B. Noise
C. Overexposure
D. Compression Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What main distortion can be seen on the bear in this image?\nA. Blur\nB. Noise\nC. Overexposure\nD. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7633,[Response]: B.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 1293:  87%|▊| 1294/1495 [07:2
[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1294:  87%|▊| 1294/1495 [07:26<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What main distortion can be seen on the bear in this image?\nA. Blur\nB. Noise\nC. Overexposure\nD. Compression Artifacts\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the athlete number 55 emphasized in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the athlete number 55 emphasized in the composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the athlete number 55 emphasized in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7635,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1294:  87%|▊| 1295/1495 [07:26<
[Running Accuracy]: 0.7637,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1295:  87%|▊| 1295/1495 [07:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the athlete number 55 emphasized in the composition of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the vehicle clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the vehicle clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7637,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1295:  87%|▊| 1296/1495 [07:26<0
[Running Accuracy]: 0.7639,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1296:  87%|▊| 1296/1495 [07:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the vehicle clear in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most serious quality issue in the image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most serious quality issue in the image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most serious quality issue in the image?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7639,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1296:  87%|▊| 1297/1495 [07:27<0
[Running Accuracy]: 0.7641,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1297:  87%|▊| 1297/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most serious quality issue in the image?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this photo?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this photo?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this photo?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7641,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1297:  87%|▊| 1298/149
[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1298:  87%|▊| 1298/1495 [07:27<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this photo?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Noise
B. Motion blur
C. Brightness
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Noise
B. Motion blur
C. Brightness
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Brightness\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7643,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1298:  87%|▊| 1299/1495 [07:28<0
[Running Accuracy]: 0.7644,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1299:  87%|▊| 1299/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Brightness\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7644,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1299:  87%|▊| 1300/1495
[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1300:  87%|▊| 1300/1495 [07:28<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How does this image look like?
A. Snowy
B. Foggy
C. Sunny
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How does this image look like?
A. Snowy
B. Foggy
C. Sunny
Answer with the option's letter from the given choices directly.

prompts: [["How does this image look like?\nA. Snowy\nB. Foggy\nC. Sunny\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1300:  87%|▊| 1301/1495 [07:28<0
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Snowy, , [Prog]: 1301:  87%|▊| 1301/1495 [07:28
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How does this image look like?\nA. Snowy\nB. Foggy\nC. Sunny\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Snowy, , [Prog]: 1301:  87%|▊| 1302/1495 [07:29
[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1302:  87%|▊| 1302/1495 [07:29<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image color full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What type of quality issues are present in the image?
A. Overexposure
B. Underexposure
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What type of quality issues are present in the image?
A. Overexposure
B. Underexposure
C. Noise
D. Out-of-focus
Answer with the option's letter from the given choices directly.

prompts: [["What type of quality issues are present in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1302:  87%|▊| 1303/1495 [07:29<0
[Running Accuracy]: 0.7644,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1303:  87%|▊| 1303/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What type of quality issues are present in the image?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the most apparent distortion for the car in the middle of this image?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the most apparent distortion for the car in the middle of this image?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which is the most apparent distortion for the car in the middle of this image?\nA. Blur\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7644,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1303:  87%|▊| 1304/1495
[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1304:  87%|▊| 1304/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the most apparent distortion for the car in the middle of this image?\nA. Blur\nB. Under-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the doors in this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the doors in this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the doors in this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7646,[Response]: B.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1304:  87%|▊| 1305/14
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1305:  87%|▊| 1305/1495 [07:31<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the doors in this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have noises or artifacts?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have noises or artifacts?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have noises or artifacts?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1305:  87%|▊| 1306/1495 [07:31<0
[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1306:  87%|▊| 1306/1495 [07:31<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image have noises or artifacts?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color of the electric vehicle in the image?
A. Yellow
B. Green
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color of the electric vehicle in the image?
A. Yellow
B. Green
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color of the electric vehicle in the image?\nA. Yellow\nB. Green\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1306:  87%|▊| 1307/1495 [07:32<0
[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 1307:  87%|▊| 1307/1495 [07:32
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main color of the electric vehicle in the image?\nA. Yellow\nB. Green\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this beach sand in this image get over-exposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this beach sand in this image get over-exposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this beach sand in this image get over-exposed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 1307:  87%|▊| 1308/1495 [07:32
[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1308:  87%|▊| 1308/1495 [07:32<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this beach sand in this image get over-exposed?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1308:  88%|▉| 1309/1495 [07:32<0
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1309:  88%|▉| 1309/1495 [07:32<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in the image?
A. Wood stick
B. Shrub
C. Wooden board in the top right corner
D. Ditch
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in the image?
A. Wood stick
B. Shrub
C. Wooden board in the top right corner
D. Ditch
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in the image?\nA. Wood stick\nB. Shrub\nC. Wooden board in the top right corner\nD. Ditch\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1309:  88%|▉| 1310/1495 [07:33<01
[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Wooden board in the top right corner, , [Prog]:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in the image?\nA. Wood stick\nB. Shrub\nC. Wooden board in the top right corner\nD. Ditch\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the dinasour toy?
A. Medium
B. Low
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the dinasour toy?
A. Medium
B. Low
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the dinasour toy?\nA. Medium\nB. Low\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7656,[Response]: C.<|endoftext|>, [Correct Ans]: Wooden board in the top right corner, , [Prog]:
[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1311:  88%|▉| 1311/1495 [07:33<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the dinasour toy?\nA. Medium\nB. Low\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7658,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1311:  88%|▉| 1312/1495 [07:34<
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1312:  88%|▉| 1312/1495 [07:34<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture blurry?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition of the picture like?
A. Diagonal
B. Centered
C. Symmetrical
D. Pyramidal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the composition of the picture like?
A. Diagonal
B. Centered
C. Symmetrical
D. Pyramidal
Answer with the option's letter from the given choices directly.

prompts: [["What is the composition of the picture like?\nA. Diagonal\nB. Centered\nC. Symmetrical\nD. Pyramidal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1312:  88%|▉| 1313/1495 [07:34<0
[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: Centered, , [Prog]: 1313:  88%|▉| 1313/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the composition of the picture like?\nA. Diagonal\nB. Centered\nC. Symmetrical\nD. Pyramidal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the clothes of the main character in the image vivid in color?
A. Vivid
B. Not vivid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the clothes of the main character in the image vivid in color?
A. Vivid
B. Not vivid
Answer with the option's letter from the given choices directly.

prompts: [["Are the clothes of the main character in the image vivid in color?\nA. Vivid\nB. Not vivid\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B. Not vivid

[Running Accuracy]: 0.7662,[Response]: B.<|endoftext|>, [Correct Ans]: Centered, , [Prog]: 1313:  88%|▉| 1314/1495 [07
[Running Accuracy]: 0.7664,[Response]: B. Not vivid<|endoftext|>, [Correct Ans]: Not vivid, , [Prog]: 1314:  88%|▉| 13
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the clothes of the main character in the image vivid in color?\nA. Vivid\nB. Not vivid\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B. Not vivid<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there a problem of image defocus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there a problem of image defocus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there a problem of image defocus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7664,[Response]: B. Not vivid<|endoftext|>, [Correct Ans]: Not vivid, , [Prog]: 1314:  88%|▉| 13
[Running Accuracy]: 0.7665,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1315:  88%|▉| 1315/1495 [07:35<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there a problem of image defocus?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman holding an umbrella in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman holding an umbrella in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman holding an umbrella in this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7665,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1315:  88%|▉| 1316/1495 [07:35<01
[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1316:  88%|▉| 1316/1495 [07:35<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the woman holding an umbrella in this image clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality of this picture?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1316:  88%|▉| 1317/1495 [07:35<01
[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1317:  88%|▉| 1317/1495 [07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality of this picture?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the noise in this picture?
A. Severe
B. Moderate
C. Mild
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the noise in this picture?
A. Severe
B. Moderate
C. Mild
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the noise in this picture?\nA. Severe\nB. Moderate\nC. Mild\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1317:  88%|▉| 1318/1495 [07:3
[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1318:  88%|▉| 1318/1495 [07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the noise in this picture?\nA. Severe\nB. Moderate\nC. Mild\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of photography effect was used in the image?
A. Motion blur
B. Bokeh
C. Black and white filter
D. Long exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of photography effect was used in the image?
A. Motion blur
B. Bokeh
C. Black and white filter
D. Long exposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of photography effect was used in the image?\nA. Motion blur\nB. Bokeh\nC. Black and white filter\nD. Long exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1318:  88%|▉| 1319/1495 [07:3
[Running Accuracy]: 0.7665,[Response]: C.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 1319:  88%|▉|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of photography effect was used in the image?\nA. Motion blur\nB. Bokeh\nC. Black and white filter\nD. Long exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Medium
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7665,[Response]: C.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 1319:  88%|▉|
[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1320:  88%|▉| 1320/1495 [07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of this image?\nA. Medium\nB. Bright\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful are the trees in this picture?
A. Colorful
B. Normal
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful are the trees in this picture?
A. Colorful
B. Normal
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful are the trees in this picture?\nA. Colorful\nB. Normal\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1320:  88%|▉| 1321/1495 [07:3
[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1321:  88%|▉| 1321/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful are the trees in this picture?\nA. Colorful\nB. Normal\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is not present in this image?
A. Out of focus
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion is not present in this image?
A. Out of focus
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion is not present in this image?\nA. Out of focus\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7661,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1321:  88%|▉| 1322/1495 [07
[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1322:  88%|▉| 1322/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is not present in this image?\nA. Out of focus\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in the image?
A. Blurry
B. Overexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issues exist in the image?
A. Blurry
B. Overexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What quality issues exist in the image?\nA. Blurry\nB. Overexposure\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7663,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1322:  88%|▉| 1323/149
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1323:  88%|▉| 1323/1495 [07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in the image?\nA. Blurry\nB. Overexposure\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is it a clear image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is it a clear image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is it a clear image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1323:  89%|▉| 1324/1495 [07:3
[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1324:  89%|▉| 1324/1495 [07:39<01
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is it a clear image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1324:  89%|▉| 1325/1495 [07:39<01
[Running Accuracy]: 0.7660,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1325:  89%|▉| 1325/1495 [07:3
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. Just fine\nB. Too dark\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1325:  89%|▉| 1326/1495 [07:3
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 1326:  89%|▉| 1326/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?\nA. Just fine\nB. Too dark\nC. Too bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image unreal?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image unreal?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image unreal?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 1326:  89%|▉| 1327/1495 [
[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1327:  89%|▉| 1327/1495 [07:40<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image unreal?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic, computer-generated, or sketch-like?
A. Sketch-like
B. Computer-generated
C. Photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic, computer-generated, or sketch-like?
A. Sketch-like
B. Computer-generated
C. Photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic, computer-generated, or sketch-like?\nA. Sketch-like\nB. Computer-generated\nC. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7664,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1327:  89%|▉| 1328/1495 [07:40<0
[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: Sketch-like, , [Prog]: 1328:  89%|▉| 1328/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic, computer-generated, or sketch-like?\nA. Sketch-like\nB. Computer-generated\nC. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?
A. The door
B. The corridor
C. The wall
D. The girl with red hair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focal point in this image?
A. The door
B. The corridor
C. The wall
D. The girl with red hair
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focal point in this image?\nA. The door\nB. The corridor\nC. The wall\nD. The girl with red hair\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7666,[Response]: A.<|endoftext|>, [Correct Ans]: Sketch-like, , [Prog]: 1328:  89%|▉| 1329/1495 
[Running Accuracy]: 0.7667,[Response]: D.<|endoftext|>, [Correct Ans]: The girl with red hair, , [Prog]: 1329:  89%|▉|
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the focal point in this image?\nA. The door\nB. The corridor\nC. The wall\nD. The girl with red hair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the leaf's texture in this image?
A. Low
B. Meidum
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the leaf's texture in this image?
A. Low
B. Meidum
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the leaf's texture in this image?\nA. Low\nB. Meidum\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7667,[Response]: D.<|endoftext|>, [Correct Ans]: The girl with red hair, , [Prog]: 1329:  89%|▉|
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Meidum, , [Prog]: 1330:  89%|▉| 1330/1495 [07:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the leaf's texture in this image?\nA. Low\nB. Meidum\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in the night sky on the top of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any noise in the night sky on the top of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise in the night sky on the top of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Meidum, , [Prog]: 1330:  89%|▉| 1331/1495 [07:4
[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1331:  89%|▉| 1331/1495 [07:41<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any noise in the night sky on the top of the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the main subject in the image?
A. Overexposed
B. Properly exposed
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of the main subject in the image?
A. Overexposed
B. Properly exposed
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of the main subject in the image?\nA. Overexposed\nB. Properly exposed\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1331:  89%|▉| 1332/1495 [07:41<0
[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1332:  89%|▉| 1332/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of the main subject in the image?\nA. Overexposed\nB. Properly exposed\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting sufficient in the image?
A. Too bright
B. Too dark
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting sufficient in the image?
A. Too bright
B. Too dark
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting sufficient in the image?\nA. Too bright\nB. Too dark\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1332:  89%|▉| 1333/1495
[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1333:  89%|▉| 1333/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting sufficient in the image?\nA. Too bright\nB. Too dark\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image is emphasized in the center of the image composition?
A. Buildings
B. Black boat
C. Green boat
D. Red boat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image is emphasized in the center of the image composition?
A. Buildings
B. Black boat
C. Green boat
D. Red boat
Answer with the option's letter from the given choices directly.

prompts: [["Which image is emphasized in the center of the image composition?\nA. Buildings\nB. Black boat\nC. Green boat\nD. Red boat\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1333:  89%|▉| 1334/1495 [07
[Running Accuracy]: 0.7661,[Response]: D.<|endoftext|>, [Correct Ans]: Red boat, , [Prog]: 1334:  89%|▉| 1334/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image is emphasized in the center of the image composition?\nA. Buildings\nB. Black boat\nC. Green boat\nD. Red boat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: D.<|endoftext|>, [Correct Ans]: Red boat, , [Prog]: 1334:  89%|▉| 1335/1495 [07
[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1335:  89%|▉| 1335/1495 [07:42<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is the flower in this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is the flower in this picture?
A. Normal
B. Colorful
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is the flower in this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1335:  89%|▉| 1336/1495 [07:43<
[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1336:  89%|▉| 1336/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is the flower in this picture?\nA. Normal\nB. Colorful\nC. Dull\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this a clear image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this a clear image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this a clear image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1336:  89%|▉| 1337/1495 [07
[Running Accuracy]: 0.7659,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1337:  89%|▉| 1337/1495 [07:43<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this a clear image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the girl's clothing the most colorful part of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the girl's clothing the most colorful part of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the girl's clothing the most colorful part of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7659,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1337:  89%|▉| 1338/1495 [07:43<0
[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1338:  89%|▉| 1338/1495 [07:43<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the girl's clothing the most colorful part of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1338:  90%|▉| 1339/1495 [07:44<00
[Running Accuracy]: 0.7655,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1339:  90%|▉| 1339/1495 [07:44<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture in focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7655,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1339:  90%|▉| 1340/1495 [07:44<0
[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1340:  90%|▉| 1340/1495 [07:44<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture in focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus of the image correct?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus of the image correct?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus of the image correct?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1340:  90%|▉| 1341/1495 [07:44<00
[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1341:  90%|▉| 1341/1495 [07:44<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the focus of the image correct?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?
A. Chair
B. Tall glass
C. Woman
D. Bracelet
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest object in the image?
A. Chair
B. Tall glass
C. Woman
D. Bracelet
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest object in the image?\nA. Chair\nB. Tall glass\nC. Woman\nD. Bracelet\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7658,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1341:  90%|▉| 1342/1495 [07:45<0
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Tall glass, , [Prog]: 1342:  90%|▉| 1342/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest object in the image?\nA. Chair\nB. Tall glass\nC. Woman\nD. Bracelet\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image full?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Tall glass, , [Prog]: 1342:  90%|▉| 1343/1495 [
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1343:  90%|▉| 1343/1495 [07:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the image full?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture contain noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture contain noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture contain noise?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1343:  90%|▉| 1344/1495 [07:45<0
[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1344:  90%|▉| 1344/1495 [07:45<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this picture contain noise?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this image?
A. Overexposure
B. Out of focus
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in this image?
A. Overexposure
B. Out of focus
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in this image?\nA. Overexposure\nB. Out of focus\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1344:  90%|▉| 1345/1495 [07:46<0
[Running Accuracy]: 0.7643,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1345:  90%|▉| 1345/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in this image?\nA. Overexposure\nB. Out of focus\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the parachute in this image?
A. Vibrant
B. Faded
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the parachute in this image?
A. Vibrant
B. Faded
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the parachute in this image?\nA. Vibrant\nB. Faded\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7643,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1345:  90%|▉| 1346/1495
[Running Accuracy]: 0.7645,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1346:  90%|▉| 1346/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the parachute in this image?\nA. Vibrant\nB. Faded\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the details of the bird's face clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the details of the bird's face clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the details of the bird's face clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7645,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1346:  90%|▉| 1347/1495 [07:
[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1347:  90%|▉| 1347/1495 [07:46<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the details of the bird's face clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1347:  90%|▉| 1348/1495 [07:47<00
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1348:  90%|▉| 1348/1495 [07:47<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image out of focus?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background of this image blurred?
A. Severely
B. Slightly
C. Moderately
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the background of this image blurred?
A. Severely
B. Slightly
C. Moderately
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the background of this image blurred?\nA. Severely\nB. Slightly\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1348:  90%|▉| 1349/1495 [07:47<0
[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 1349:  90%|▉| 1349/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>To what extent is the background of this image blurred?\nA. Severely\nB. Slightly\nC. Moderately\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flower bed in this image?
A. Vibrant
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the flower bed in this image?
A. Vibrant
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the flower bed in this image?\nA. Vibrant\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7650,[Response]: A.<|endoftext|>, [Correct Ans]: Severely, , [Prog]: 1349:  90%|▉| 1350/1495 [07
[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1350:  90%|▉| 1350/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the flower bed in this image?\nA. Vibrant\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main object in the image?
A. Rider
B. Sun
C. Car
D. Bird
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main object in the image?
A. Rider
B. Sun
C. Car
D. Bird
Answer with the option's letter from the given choices directly.

prompts: [["What is the main object in the image?\nA. Rider\nB. Sun\nC. Car\nD. Bird\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1350:  90%|▉| 1351/1495 [07:
[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Rider, , [Prog]: 1351:  90%|▉| 1351/1495 [07:48
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main object in the image?\nA. Rider\nB. Sun\nC. Car\nD. Bird\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Rider, , [Prog]: 1351:  90%|▉| 1352/1495 [07:48
[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1352:  90%|▉| 1352/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Motion blur\nB. Overexposure\nC. Underexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7648,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1352:  91%|▉| 1353/1495 
[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1353:  91%|▉| 1353/1495 [07:48<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does not exist in this image?
A. Noise
B. Out of focus
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7650,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1353:  91%|▉| 1354/1495 [07:49<0
[Running Accuracy]: 0.7651,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1354:  91%|▉| 1354/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image quality?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7651,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1354:  91%|▉| 1355/149
[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1355:  91%|▉| 1355/1495 [07:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image quality?\nA. Good\nB. Average\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Motion blur
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1355:  91%|▉| 1356/1495 [07:
[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1356:  91%|▉| 1356/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear and sharp?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear and sharp?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1356:  91%|▉| 1357/1495
[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1357:  91%|▉| 1357/1495 [07:50<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is most severe in this image?
A. Blur
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion is most severe in this image?
A. Blur
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion is most severe in this image?\nA. Blur\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1357:  91%|▉| 1358/1495 [07:50<00
[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1358:  91%|▉| 1358/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion is most severe in this image?\nA. Blur\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?
A. Ground
B. Moon
C. Person
D. Stars
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Ground
B. Moon
C. Person
D. Stars
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Ground\nB. Moon\nC. Person\nD. Stars\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7651,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1358:  91%|▉| 1359/149
[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Moon, , [Prog]: 1359:  91%|▉| 1359/1495 [07:51<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part in this image?\nA. Ground\nB. Moon\nC. Person\nD. Stars\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the saturation of the image?
A. Average
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7653,[Response]: B.<|endoftext|>, [Correct Ans]: Moon, , [Prog]: 1359:  91%|▉| 1360/1495 [07:51<
[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1360:  91%|▉| 1360/1495 [07:51<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the saturation of the image?\nA. Average\nB. Good\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of this photo very high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clarity of this photo very high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the clarity of this photo very high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1360:  91%|▉| 1361/1495 [07:51<
[Running Accuracy]: 0.7656,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1361:  91%|▉| 1361/1495 [07:51<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the clarity of this photo very high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look foggy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look foggy?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look foggy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7656,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1361:  91%|▉| 1362/1495 [07:52<00
[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1362:  91%|▉| 1362/1495 [07:52<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look foggy?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the most clear in the image?
A. Forest
B. Fox
C. River
D. People
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the most clear in the image?
A. Forest
B. Fox
C. River
D. People
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the most clear in the image?\nA. Forest\nB. Fox\nC. River\nD. People\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7658,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1362:  91%|▉| 1363/1495 [07:52<0
[Running Accuracy]: 0.7660,[Response]: D.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1363:  91%|▉| 1363/1495 [07:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is the most clear in the image?\nA. Forest\nB. Fox\nC. River\nD. People\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the cow in the picture?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the cow in the picture?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the cow in the picture?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: D.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1363:  91%|▉| 1364/1495 [07:5
[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1364:  91%|▉| 1364/1495 [07:52<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the cow in the picture?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Blurry\nB. Clear\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7661,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1364:  91%|▉| 1365/1495 [07:53<
[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1365:  91%|▉| 1365/1495 [07:53
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the image clarity?\nA. Blurry\nB. Clear\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the person in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1365:  91%|▉| 1366/1495 [07:53
[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1366:  91%|▉| 1366/1495 [07:53<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the person in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background vegetation in the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background vegetation in the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background vegetation in the image?\nA. Moderate\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7657,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1366:  91%|▉| 1367/1495 [07:53<0
[Running Accuracy]: 0.7652,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1367:  91%|▉| 1367/1495 [07:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the background vegetation in the image?\nA. Moderate\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is present in this image?
A. Out of Focus
B. Motion Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion is present in this image?
A. Out of Focus
B. Motion Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion is present in this image?\nA. Out of Focus\nB. Motion Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7652,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1367:  92%|▉| 1368/1495 [07:5
[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1368:  92%|▉| 1368/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of distortion is present in this image?\nA. Out of Focus\nB. Motion Blur\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant in the image?
A. The clothes of the person on the left
B. The clothes of the person on the right
C. The hand of the person on the left
D. The background behind the person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most vibrant in the image?
A. The clothes of the person on the left
B. The clothes of the person on the right
C. The hand of the person on the left
D. The background behind the person
Answer with the option's letter from the given choices directly.

prompts: [["What is the most vibrant in the image?\nA. The clothes of the person on the left\nB. The clothes of the person on the right\nC. The hand of the person on the left\nD. The background behind the person\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7646,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1368:  92%|▉| 1369/1495 
[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: The clothes of the person on the right, , [Prog
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the most vibrant in the image?\nA. The clothes of the person on the left\nB. The clothes of the person on the right\nC. The hand of the person on the left\nD. The background behind the person\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the subject - the rabbit in the image?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the subject - the rabbit in the image?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the subject - the rabbit in the image?\nA. Low\nB. Moderate\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7648,[Response]: B.<|endoftext|>, [Correct Ans]: The clothes of the person on the right, , [Prog
[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1370:  92%|▉| 1370/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color saturation of the subject - the rabbit in the image?\nA. Low\nB. Moderate\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Somewhat blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Very blurry
C. Somewhat blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1370:  92%|▉| 1371/1495 [07
[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1371:  92%|▉| 1371/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Very blurry\nC. Somewhat blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How good is the composition of this picture?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How good is the composition of this picture?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1371:  92%|▉| 1372/1495 
[Running Accuracy]: 0.7638,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1372:  92%|▉| 1372/1495 [07:55<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How good is the composition of this picture?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Normal
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Normal
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Normal\nB. Clear\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7638,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1372:  92%|▉| 1373/1495 [07:55<
[Running Accuracy]: 0.7640,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1373:  92%|▉| 1373/1495 [07:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Normal\nB. Clear\nC. Blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the contrast of this picture high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the contrast of this picture high?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the contrast of this picture high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7640,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1373:  92%|▉| 1374/1495 [07:5
[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1374:  92%|▉| 1374/1495 [07:56<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the contrast of this picture high?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1374:  92%|▉| 1375/1495 [07:56<00
[Running Accuracy]: 0.7636,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1375:  92%|▉| 1375/1495 [07:56<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degradation occurs in the photo?
A. Motion Blur
B. Defocus Blur
C. Flicker
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degradation occurs in the photo?
A. Motion Blur
B. Defocus Blur
C. Flicker
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What degradation occurs in the photo?\nA. Motion Blur\nB. Defocus Blur\nC. Flicker\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7636,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1375:  92%|▉| 1376/1495 [07:56<
[Running Accuracy]: 0.7638,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1376:  92%|▉| 1376/1495 [07:56
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What degradation occurs in the photo?\nA. Motion Blur\nB. Defocus Blur\nC. Flicker\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the man in the image look real?
A. Not real
B. Real
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the man in the image look real?
A. Not real
B. Real
Answer with the option's letter from the given choices directly.

prompts: [["Does the man in the image look real?\nA. Not real\nB. Real\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7638,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1376:  92%|▉| 1377/1495 [07:57
[Running Accuracy]: 0.7640,[Response]: A.<|endoftext|>, [Correct Ans]: Not real, , [Prog]: 1377:  92%|▉| 1377/1495 [07
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the man in the image look real?\nA. Not real\nB. Real\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the jellyfish aesthetically beautiful in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the jellyfish aesthetically beautiful in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the jellyfish aesthetically beautiful in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7640,[Response]: A.<|endoftext|>, [Correct Ans]: Not real, , [Prog]: 1377:  92%|▉| 1378/1495 [07
[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1378:  92%|▉| 1378/1495 [07:57<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the jellyfish aesthetically beautiful in this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does the image not have?
A. Overexposure
B. Noise
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality issue does the image not have?
A. Overexposure
B. Noise
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue does the image not have?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1378:  92%|▉| 1379/1495 [07:57<0
[Running Accuracy]: 0.7636,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1379:  92%|▉| 1379/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which quality issue does the image not have?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7636,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1379:  92%|▉| 1380/1495 
[Running Accuracy]: 0.7638,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1380:  92%|▉| 1380/1495 [07:58<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the flowers in this image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image look noisy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image look noisy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image look noisy?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7638,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1380:  92%|▉| 1381/1495 [07:58<00
[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1381:  92%|▉| 1381/1495 [07:58<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image look noisy?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the dog contain clear texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the dog contain clear texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the dog contain clear texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7639,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1381:  92%|▉| 1382/1495 [07:58<0
[Running Accuracy]: 0.7634,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1382:  92%|▉| 1382/1495 [07:58<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the dog contain clear texture?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two wrestlers in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two wrestlers in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the two wrestlers in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7634,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1382:  93%|▉| 1383/1495 [07:59<00
[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1383:  93%|▉| 1383/1495 [07:59<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the two wrestlers in this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?
A. Rock
B. People
C. Mountain
D. Coin
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Rock
B. People
C. Mountain
D. Coin
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Rock\nB. People\nC. Mountain\nD. Coin\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7636,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1383:  93%|▉| 1384/1495 [07:59<0
[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1384:  93%|▉| 1384/1495 [07:5
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?\nA. Rock\nB. People\nC. Mountain\nD. Coin\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7637,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1384:  93%|▉| 1385/1495 [07:5
[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1385:  93%|▉| 1385/1495 [07:59<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of the image?\nA. Good\nB. Fair\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the feathers on the swan in the image the clearest?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the feathers on the swan in the image the clearest?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the feathers on the swan in the image the clearest?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7639,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1385:  93%|▉| 1386/1495 [08:00<
[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1386:  93%|▉| 1386/1495 [08:00<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the feathers on the swan in the image the clearest?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast level of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level of the image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7641,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1386:  93%|▉| 1387/1495 [08:00<0
[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1387:  93%|▉| 1387/1495 [08:00<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the contrast level of the image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the corn in the image high?
A. Low
B. High
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the corn in the image high?
A. Low
B. High
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the corn in the image high?\nA. Low\nB. High\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7642,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1387:  93%|▉| 1388/1495 [08:00<0
[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1388:  93%|▉| 1388/1495 [08:00<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color saturation of the corn in the image high?\nA. Low\nB. High\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the butterflies of this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the butterflies of this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the butterflies of this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7644,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1388:  93%|▉| 1389/1495 [08:01<
[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1389:  93%|▉| 1389/1495 [08:01<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the butterflies of this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the main distortion that mostly affects the quality of this image?
A. Blur
B. Low light
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the main distortion that mostly affects the quality of this image?
A. Blur
B. Low light
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which is the main distortion that mostly affects the quality of this image?\nA. Blur\nB. Low light\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A

[Running Accuracy]: 0.7646,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1389:  93%|▉| 1390/1495 [08:01<
[Running Accuracy]: 0.7647,[Response]: A<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1390:  93%|▉| 1390/1495 [08:01<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which is the main distortion that mostly affects the quality of this image?\nA. Blur\nB. Low light\nC. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7647,[Response]: A<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1390:  93%|▉| 1391/1495 [08:02<0
[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1391:  93%|▉| 1391/1495 [08:02<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters in the image clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7649,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1391:  93%|▉| 1392/1495 [08:02<00
[Running Accuracy]: 0.7651,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1392:  93%|▉| 1392/1495 [08:02<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting in this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting in this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting in this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7651,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1392:  93%|▉| 1393/1495 [08:02<00
[Running Accuracy]: 0.7645,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1393:  93%|▉| 1393/1495 [08:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What do you think of the lighting in this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpness of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7645,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1393:  93%|▉| 1394/1495 [08:0
[Running Accuracy]: 0.7647,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1394:  93%|▉| 1394/1495 [08:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of this image?
A. Dim
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of this image?
A. Dim
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of this image?\nA. Dim\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7647,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1394:  93%|▉| 1395/1495 [08:0
[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 1395:  93%|▉| 1395/1495 [08:03<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting condition of this image?\nA. Dim\nB. Medium\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the little dog in the picture?
A. Poor
B. Normal
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the little dog in the picture?
A. Poor
B. Normal
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the little dog in the picture?\nA. Poor\nB. Normal\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7649,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 1395:  93%|▉| 1396/1495 [08:03<0
[Running Accuracy]: 0.7650,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1396:  93%|▉| 1396/1495 [08:03<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation of the little dog in the picture?\nA. Poor\nB. Normal\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there dynamic blur in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there dynamic blur in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there dynamic blur in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7650,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1396:  93%|▉| 1397/1495 [08:04<
[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1397:  93%|▉| 1397/1495 [08:04<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there dynamic blur in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the grass real in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the grass real in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the grass real in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7652,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1397:  94%|▉| 1398/1495 [08:04<00
[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1398:  94%|▉| 1398/1495 [08:04<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the grass real in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters on the TV in this picture?
A. Fair
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters on the TV in this picture?
A. Fair
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters on the TV in this picture?\nA. Fair\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7654,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1398:  94%|▉| 1399/1495 [08:05<00
[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1399:  94%|▉| 1399/1495 [08:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear are the characters on the TV in this picture?\nA. Fair\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest part in the image?
A. Utensils
B. Sink
C. Bowl
D. Person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest part in the image?
A. Utensils
B. Sink
C. Bowl
D. Person
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest part in the image?\nA. Utensils\nB. Sink\nC. Bowl\nD. Person\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7655,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1399:  94%|▉| 1400/1495 [08:0
[Running Accuracy]: 0.7657,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1400:  94%|▉| 1400/1495 [08:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the sharpest part in the image?\nA. Utensils\nB. Sink\nC. Bowl\nD. Person\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image distortion serious?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image distortion serious?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["Is the image distortion serious?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7657,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1400:  94%|▉| 1401/1495 [08:0
[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1401:  94%|▉| 1401/1495 [08:0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image distortion serious?\nA. Severe\nB. Moderate\nC. Slight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7659,[Response]: C.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 1401:  94%|▉| 1402/1495 [08:0
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1402:  94%|▉| 1402/1495 [08:06<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1402:  94%|▉| 1403/1495 [08:06<00
[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1403:  94%|▉| 1403/1495 [08:06<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture colorful?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the underwear in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the underwear in this image vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the underwear in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A. No

[Running Accuracy]: 0.7662,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1403:  94%|▉| 1404/1495 [08:06<00
[Running Accuracy]: 0.7664,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 1404:  94%|▉| 1404/1495 [08:06
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the color of the underwear in this image vibrant?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A. No<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?
A. Under-exposure
B. Appropriate
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of this image?
A. Under-exposure
B. Appropriate
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of this image?\nA. Under-exposure\nB. Appropriate\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7664,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 1404:  94%|▉| 1405/1495 [08:07
[Running Accuracy]: 0.7665,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1405:  94%|▉| 1405/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the exposure of this image?\nA. Under-exposure\nB. Appropriate\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the human in this image?
A. Bright
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the human in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7665,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 1405:  94%|▉| 1406/149
[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1406:  94%|▉| 1406/1495 [08:07<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the lighting of the human in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7660,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1406:  94%|▉| 1407/1495 [08:07<
[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1407:  94%|▉| 1407/1495 [08:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color saturation in the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this beach rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this beach rich in texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this beach rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7662,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1407:  94%|▉| 1408/1495 [08:08<
[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1408:  94%|▉| 1408/1495 [08:08<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this beach rich in texture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the car light in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the car light in the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the car light in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7663,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1408:  94%|▉| 1409/1495 [08:08<00
[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1409:  94%|▉| 1409/1495 [08:08<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the car light in the image?\nA. Poor\nB. Good\nC. Average\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced for the human in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting well-balanced for the human in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced for the human in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7665,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1409:  94%|▉| 1410/1495 [08:09<
[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1410:  94%|▉| 1410/1495 [08:09<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the lighting well-balanced for the human in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?
A. Blurry
B. Normal
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Normal
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Normal\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7667,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1410:  94%|▉| 1411/1495 [08:09<0
[Running Accuracy]: 0.7668,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1411:  94%|▉| 1411/1495 [08:09
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is this picture?\nA. Blurry\nB. Normal\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the saturation of the people in the image the highest?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the saturation of the people in the image the highest?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the saturation of the people in the image the highest?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7668,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1411:  94%|▉| 1412/1495 [08:09
[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1412:  94%|▉| 1412/1495 [08:09<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the saturation of the people in the image the highest?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the robot closest to the picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the robot closest to the picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the robot closest to the picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7670,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1412:  95%|▉| 1413/1495 [08:10<0
[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1413:  95%|▉| 1413/1495 [08:10<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the robot closest to the picture clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?
A. Photo-realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic or computer-generated?
A. Photo-realistic
B. Computer-generated
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic or computer-generated?\nA. Photo-realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4375], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7672,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1413:  95%|▉| 1414/1495 [08:10<0
[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1414:  95%|▉| 141
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look photo-realistic or computer-generated?\nA. Photo-realistic\nB. Computer-generated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?
A. Noise
B. Compression Artifact
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Noise
B. Compression Artifact
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Noise\nB. Compression Artifact\nC. Blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7673,[Response]: B.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1414:  95%|▉| 141
[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1415:  95%|▉| 1415/1495 [08:10
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the major distortion in this image?\nA. Noise\nB. Compression Artifact\nC. Blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurred due to motion?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1415:  95%|▉| 1416/1495 [08:11
[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1416:  95%|▉| 1416/1495 [08:11<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the image blurred due to motion?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in the picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1416:  95%|▉| 1417/1495 [08:11<00
[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1417:  95%|▉| 1417/1495 [08:11<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the people in the picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is it too dark to see the details of the car in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is it too dark to see the details of the car in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is it too dark to see the details of the car in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7678,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1417:  95%|▉| 1418/1495 [08:12<0
[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1418:  95%|▉| 1418/1495 [08:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is it too dark to see the details of the car in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1418:  95%|▉| 1419/1495 [08:12<0
[Running Accuracy]: 0.7681,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1419:  95%|▉| 1419/1495 [08:12<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the brightest?
A. Building
B. Sky
C. Statue
D. Staircase
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the brightest?
A. Building
B. Sky
C. Statue
D. Staircase
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the brightest?\nA. Building\nB. Sky\nC. Statue\nD. Staircase\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7681,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1419:  95%|▉| 1420/1495 [08:12<00
[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1420:  95%|▉| 1420/1495 [08:12<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the brightest?\nA. Building\nB. Sky\nC. Statue\nD. Staircase\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the clearest?
A. Tree branch
B. Forest
C. Blueberry
D. Leaf
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the clearest?
A. Tree branch
B. Forest
C. Blueberry
D. Leaf
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the clearest?\nA. Tree branch\nB. Forest\nC. Blueberry\nD. Leaf\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1420:  95%|▉| 1421/1495 [08:13<0
[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Blueberry, , [Prog]: 1421:  95%|▉| 1421/1495 [0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which part of the image is the clearest?\nA. Tree branch\nB. Forest\nC. Blueberry\nD. Leaf\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not the main distortion in this picture?
A. Noise
B. Overexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is not the main distortion in this picture?
A. Noise
B. Overexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is not the main distortion in this picture?\nA. Noise\nB. Overexposure\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Blueberry, , [Prog]: 1421:  95%|▉| 1422/1495 [0
[Running Accuracy]: 0.7679,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1422:  95%|▉| 1422/1495 [08:13
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is not the main distortion in this picture?\nA. Noise\nB. Overexposure\nC. Motion blur\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the building in this photo?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the building in this photo?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the building in this photo?\nA. Bright\nB. Dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7679,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1422:  95%|▉| 1423/1495 [08:13
[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1423:  95%|▉| 1423/1495 [08:13<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the building in this photo?\nA. Bright\nB. Dark\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does not exist in this image?
A. Noise
B. Blur
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does not exist in this image?
A. Noise
B. Blur
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does not exist in this image?\nA. Noise\nB. Blur\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1423:  95%|▉| 1424/1495 [08:14<
[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1424:  95%|▉| 1424/14
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What distortion does not exist in this image?\nA. Noise\nB. Blur\nC. Under-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is being emphasized in the composition of the image?
A. Man holding a child
B. Couple on the right side
C. Little horse
D. Tree on the left side
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is being emphasized in the composition of the image?
A. Man holding a child
B. Couple on the right side
C. Little horse
D. Tree on the left side
Answer with the option's letter from the given choices directly.

prompts: [["Which object is being emphasized in the composition of the image?\nA. Man holding a child\nB. Couple on the right side\nC. Little horse\nD. Tree on the left side\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7031], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1424:  95%|▉| 1425/14
[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: Little horse, , [Prog]: 1425:  95%|▉| 1425/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is being emphasized in the composition of the image?\nA. Man holding a child\nB. Couple on the right side\nC. Little horse\nD. Tree on the left side\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: Little horse, , [Prog]: 1425:  95%|▉| 1426/1495
[Running Accuracy]: 0.7686,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1426:  95%|▉| 1426/1495 [08:14<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is composed in the center of the image?
A. The trees
B. The leaves
C. The squirrel
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is composed in the center of the image?
A. The trees
B. The leaves
C. The squirrel
Answer with the option's letter from the given choices directly.

prompts: [["What is composed in the center of the image?\nA. The trees\nB. The leaves\nC. The squirrel\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3125], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7686,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1426:  95%|▉| 1427/1495 [08:15<
[Running Accuracy]: 0.7687,[Response]: C.<|endoftext|>, [Correct Ans]: The squirrel, , [Prog]: 1427:  95%|▉| 1427/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is composed in the center of the image?\nA. The trees\nB. The leaves\nC. The squirrel\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in this image?
A. Motion blur
B. Noise
C. Compression
D. Glare
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issues exist in this image?
A. Motion blur
B. Noise
C. Compression
D. Glare
Answer with the option's letter from the given choices directly.

prompts: [["What quality issues exist in this image?\nA. Motion blur\nB. Noise\nC. Compression\nD. Glare\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.2188], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7687,[Response]: C.<|endoftext|>, [Correct Ans]: The squirrel, , [Prog]: 1427:  96%|▉| 1428/1495
[Running Accuracy]: 0.7689,[Response]: D.<|endoftext|>, [Correct Ans]: Glare, , [Prog]: 1428:  96%|▉| 1428/1495 [08:15
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What quality issues exist in this image?\nA. Motion blur\nB. Noise\nC. Compression\nD. Glare\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in the image?
A. Noise
B. Overexposure
C. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues does not exist in the image?
A. Noise
B. Overexposure
C. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues does not exist in the image?\nA. Noise\nB. Overexposure\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7689,[Response]: D.<|endoftext|>, [Correct Ans]: Glare, , [Prog]: 1428:  96%|▉| 1429/1495 [08:16
[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1429:  96%|▉| 1429/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality issues does not exist in the image?\nA. Noise\nB. Overexposure\nC. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1429:  96%|▉| 1430/1495
[Running Accuracy]: 0.7692,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1430:  96%|▉| 1430/1495 [08:16<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image quality problem does not exist in this image?
A. Overexposure
B. Noise
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image quality problem does not exist in this image?
A. Overexposure
B. Noise
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which image quality problem does not exist in this image?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7692,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1430:  96%|▉| 1431/1495 [08:16<0
[Running Accuracy]: 0.7687,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1431:  96%|▉| 1431/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which image quality problem does not exist in this image?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Underexposure
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Underexposure
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7687,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1431:  96%|▉| 1432/1495
[Running Accuracy]: 0.7689,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1432:  96%|▉| 1432/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7689,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1432:  96%|▉| 1433/1495 
[Running Accuracy]: 0.7690,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1433:  96%|▉| 1433/1495 [08:17<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>High is the lighting of the buildings in this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
High is the lighting of the buildings in this image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["High is the lighting of the buildings in this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7690,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1433:  96%|▉| 1434/1495 [08:17<0
[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1434:  96%|▉| 1434/1495 [08:17<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>High is the lighting of the buildings in this image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear and sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear and sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4844], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7692,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1434:  96%|▉| 1435/1495 [08:18<
[Running Accuracy]: 0.7693,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1435:  96%|▉| 1435/1495 [08:18<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image clear and sharp?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look dynamic or static?
A. Dynamic
B. Static
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look dynamic or static?
A. Dynamic
B. Static
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look dynamic or static?\nA. Dynamic\nB. Static\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0156], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7693,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1435:  96%|▉| 1436/1495 [08:18<00
[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Dynamic, , [Prog]: 1436:  96%|▉| 1436/1495 [08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image look dynamic or static?\nA. Dynamic\nB. Static\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light of the image come?
A. From above
B. From below
C. From below and to the side
D. From above and to the side
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light of the image come?
A. From above
B. From below
C. From below and to the side
D. From above and to the side
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light of the image come?\nA. From above\nB. From below\nC. From below and to the side\nD. From above and to the side\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Dynamic, , [Prog]: 1436:  96%|▉| 1437/1495 [08:
[Running Accuracy]: 0.7690,[Response]: A.<|endoftext|>, [Correct Ans]: From above and to the side, , [Prog]: 1437:  96
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>From which direction does the light of the image come?\nA. From above\nB. From below\nC. From below and to the side\nD. From above and to the side\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main color tone of flowers in the image green?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main color tone of flowers in the image green?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main color tone of flowers in the image green?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7690,[Response]: A.<|endoftext|>, [Correct Ans]: From above and to the side, , [Prog]: 1437:  96
[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1438:  96%|▉| 1438/1495 [08:19<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main color tone of flowers in the image green?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the brightest part of the image a tomato?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the brightest part of the image a tomato?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the brightest part of the image a tomato?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1438:  96%|▉| 1439/1495 [08:19<00
[Running Accuracy]: 0.7693,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1439:  96%|▉| 1439/1495 [08:19<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the brightest part of the image a tomato?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any compression distortion in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any compression distortion in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any compression distortion in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7693,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1439:  96%|▉| 1440/1495 [08:19<0
[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1440:  96%|▉| 1440/1495 [08:19<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is there any compression distortion in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How vibrant is the color of the lotus leaf in this image?
A. Vibrant
B. Dull
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How vibrant is the color of the lotus leaf in this image?
A. Vibrant
B. Dull
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How vibrant is the color of the lotus leaf in this image?\nA. Vibrant\nB. Dull\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1440:  96%|▉| 1441/1495 [08:20<0
[Running Accuracy]: 0.7689,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1441:  96%|▉| 1441/1495 [08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How vibrant is the color of the lotus leaf in this image?\nA. Vibrant\nB. Dull\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?
A. Underexposure
B. Out of focus
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality problems does not exist in this image?
A. Underexposure
B. Out of focus
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality problems does not exist in this image?\nA. Underexposure\nB. Out of focus\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7689,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1441:  96%|▉| 1442/1495 [08:
[Running Accuracy]: 0.7684,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1442:  96%|▉| 1442/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following image quality problems does not exist in this image?\nA. Underexposure\nB. Out of focus\nC. Noise\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this lighting of this image good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this lighting of this image good?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this lighting of this image good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7684,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1442:  97%|▉| 1443/149
[Running Accuracy]: 0.7685,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1443:  97%|▉| 1443/1495 [08:21<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this lighting of this image good?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues exist in the image?
A. Motion blur
B. Reflection
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues exist in the image?
A. Motion blur
B. Reflection
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What issues exist in the image?\nA. Motion blur\nB. Reflection\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7685,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1443:  97%|▉| 1444/1495 [08:21<0
[Running Accuracy]: 0.7680,[Response]: D.<|endoftext|>, [Correct Ans]: Reflection, , [Prog]: 1444:  97%|▉| 1444/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What issues exist in the image?\nA. Motion blur\nB. Reflection\nC. Underexposure\nD. Out of focus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background blurred in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the background blurred in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the background blurred in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5000], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7680,[Response]: D.<|endoftext|>, [Correct Ans]: Reflection, , [Prog]: 1444:  97%|▉| 1445/1495 [
[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1445:  97%|▉| 1445/1495 [08:21<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the background blurred in this image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of this image?
A. Window
B. Glass
C. Girl
D. Wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part of this image?
A. Window
B. Glass
C. Girl
D. Wall
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part of this image?\nA. Window\nB. Glass\nC. Girl\nD. Wall\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7682,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1445:  97%|▉| 1446/1495 [08:22<0
[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1446:  97%|▉| 1446/1495 [08:22<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the brightest part of this image?\nA. Window\nB. Glass\nC. Girl\nD. Wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the moth in this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the moth in this picture?
A. Normal
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the moth in this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7683,[Response]: C.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1446:  97%|▉| 1447/1495 [08:22<
[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1447:  97%|▉| 1447/1495 [08:22
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How clear is the moth in this picture?\nA. Normal\nB. Blurry\nC. Clear\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1447:  97%|▉| 1448/1495 [08:22
[Running Accuracy]: 0.7686,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1448:  97%|▉| 1448/1495 [08:22<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture bright?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically pleasing in terms of composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically pleasing in terms of composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically pleasing in terms of composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8438], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7686,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1448:  97%|▉| 1449/1495 [08:23<00
[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1449:  97%|▉| 1449/1495 [08:23<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image aesthetically pleasing in terms of composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is the bird in this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is the bird in this picture?
A. Colorful
B. Dull
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is the bird in this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1449:  97%|▉| 1450/1495 [08:23<0
[Running Accuracy]: 0.7690,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1450:  97%|▉| 1450/1495 [08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How colorful is the bird in this picture?\nA. Colorful\nB. Dull\nC. Normal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Underexposure
B. Overexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Underexposure
B. Overexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7690,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1450:  97%|▉| 1451/1495 [08
[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1451:  97%|▉| 1451/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Out of focus\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the sky in this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is the sky in this picture?
A. Dark
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the sky in this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7684,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1451:  97%|▉| 1452/1495 
[Running Accuracy]: 0.7686,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1452:  97%|▉| 1452/1495 [08:24<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is the sky in this picture?\nA. Dark\nB. Normal\nC. Bright\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?
A. woman
B. telephone
C. cabinet
D. calendar
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the composition of the image?
A. woman
B. telephone
C. cabinet
D. calendar
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. woman\nB. telephone\nC. cabinet\nD. calendar\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7686,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1452:  97%|▉| 1453/1495 [08:24<
[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 1453:  97%|▉| 1453/1495 [08:24
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which object is emphasized in the composition of the image?\nA. woman\nB. telephone\nC. cabinet\nD. calendar\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the painting clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the painting clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the painting clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0469], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7681,[Response]: B.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 1453:  97%|▉| 1454/1495 [08:24
[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1454:  97%|▉| 1454/1495 [08:24<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the painting clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of this picture's goldfish?
A. Average
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of this picture's goldfish?
A. Average
B. Vibrant
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of this picture's goldfish?\nA. Average\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7675,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1454:  97%|▉| 1455/1495 [08:25<00
[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1455:  97%|▉| 1455/1495 [08:
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of this picture's goldfish?\nA. Average\nB. Vibrant\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion pattern can be found in this image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion pattern can be found in this image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion pattern can be found in this image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7677,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1455:  97%|▉| 1456/1495 [08:
[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1456:  97%|▉| 1456/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which distortion pattern can be found in this image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image a clear image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image a clear image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image a clear image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7679,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1456:  97%|▉| 1457/1495
[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1457:  97%|▉| 1457/1495 [08:25<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image a clear image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?
A. Table
B. People
C. Chair
D. A cup of coffee
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Table
B. People
C. Chair
D. A cup of coffee
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Table\nB. People\nC. Chair\nD. A cup of coffee\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7680,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1457:  98%|▉| 1458/1495 [08:26<00
[Running Accuracy]: 0.7682,[Response]: D.<|endoftext|>, [Correct Ans]: A cup of coffee, , [Prog]: 1458:  98%|▉| 1458/1
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is emphasized in the center of this picture?\nA. Table\nB. People\nC. Chair\nD. A cup of coffee\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little boy emphasized in the center of the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little boy emphasized in the center of the composition of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the little boy emphasized in the center of the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7682,[Response]: D.<|endoftext|>, [Correct Ans]: A cup of coffee, , [Prog]: 1458:  98%|▉| 1459/1
[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1459:  98%|▉| 1459/1495 [08:26<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the little boy emphasized in the center of the composition of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the image?
A. Not blurry at all
B. Slightly blurry
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7683,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1459:  98%|▉| 1460/1495 [08:26<0
[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1460:  98%|▉| 1460/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How blurry is the image?\nA. Not blurry at all\nB. Slightly blurry\nC. Very blurry\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What  exist in the image?
A. Backlighting
B. Compression artifacts
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What  exist in the image?
A. Backlighting
B. Compression artifacts
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What  exist in the image?\nA. Backlighting\nB. Compression artifacts\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2344], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7685,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1460:  98%|▉| 1461/1495 
[Running Accuracy]: 0.7687,[Response]: A.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 1461:  98%|▉| 1461/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What  exist in the image?\nA. Backlighting\nB. Compression artifacts\nC. Overexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the textures of the worms clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the textures of the worms clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the textures of the worms clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8281], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7687,[Response]: A.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 1461:  98%|▉| 1462/1495
[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1462:  98%|▉| 1462/1495 [08:27<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the textures of the worms clear?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the wall clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters on the wall clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters on the wall clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7688,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1462:  98%|▉| 1463/1495 [08:28<00
[Running Accuracy]: 0.7690,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1463:  98%|▉| 1463/1495 [08:28<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the wall clear?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7690,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1463:  98%|▉| 1464/1495 [08:28<00
[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1464:  98%|▉| 1464/1495 [08:28<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the brightness of the image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture aesthetically pleasing in terms of composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture aesthetically pleasing in terms of composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture aesthetically pleasing in terms of composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1464:  98%|▉| 1465/1495 [08:29<
[Running Accuracy]: 0.7693,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1465:  98%|▉| 1465/1495 [08:29<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this picture aesthetically pleasing in terms of composition?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Normal
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7693,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1465:  98%|▉| 1466/1495 [08:29<0
[Running Accuracy]: 0.7688,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1466:  98%|▉| 1466/1495 [08:2
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How bright is this picture?\nA. Bright\nB. Normal\nC. Dark\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this subject in the image look photo realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this subject in the image look photo realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this subject in the image look photo realistic?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7688,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1466:  98%|▉| 1467/1495 [08:2
[Running Accuracy]: 0.7689,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1467:  98%|▉| 1467/1495 [08:29<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this subject in the image look photo realistic?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the robot emphasized in the center of the composition of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the robot emphasized in the center of the composition of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the robot emphasized in the center of the composition of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7689,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1467:  98%|▉| 1468/1495 [08:29<00
[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1468:  98%|▉| 1468/1495 [08:29<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the robot emphasized in the center of the composition of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the street signs in this image blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the street signs in this image blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the street signs in this image blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7691,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1468:  98%|▉| 1469/1495 [08:30<0
[Running Accuracy]: 0.7692,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1469:  98%|▉| 1469/1495 [08:30<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the street signs in this image blurred?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the surrounding areas of this picture clearer than the center part?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the surrounding areas of this picture clearer than the center part?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the surrounding areas of this picture clearer than the center part?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.4219], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7692,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1469:  98%|▉| 1470/1495 [08:30<0
[Running Accuracy]: 0.7694,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1470:  98%|▉| 1470/1495 [08:30<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the surrounding areas of this picture clearer than the center part?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image photo-realistic or computer-generated?
A. Computer-generated
B. Photo-realistic
Answer with the option's letter from the given choices directly.

prompts: [["Is this image photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7694,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1470:  98%|▉| 1471/1495 [08:30<00
[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1471:  98%|▉| 147
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is this image photo-realistic or computer-generated?\nA. Computer-generated\nB. Photo-realistic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have repetitive patterns?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7695,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1471:  98%|▉| 147
[Running Accuracy]: 0.7697,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1472:  98%|▉| 1472/1495 [08:31<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does the image have repetitive patterns?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Out of focus
B. Noise
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7697,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1472:  99%|▉| 1473/1495 [08:31<0
[Running Accuracy]: 0.7699,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1473:  99%|▉| 1473/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?
A. Bird
B. Tree stump
C. Hemp rope
D. Forest
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Bird
B. Tree stump
C. Hemp rope
D. Forest
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Bird\nB. Tree stump\nC. Hemp rope\nD. Forest\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3906], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7699,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1473:  99%|▉| 1474/1495
[Running Accuracy]: 0.7693,[Response]: B.<|endoftext|>, [Correct Ans]: Bird, , [Prog]: 1474:  99%|▉| 1474/1495 [08:32<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clearest object in the image?\nA. Bird\nB. Tree stump\nC. Hemp rope\nD. Forest\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the signs clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the signs clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the signs clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7693,[Response]: B.<|endoftext|>, [Correct Ans]: Bird, , [Prog]: 1474:  99%|▉| 1475/1495 [08:32<
[Running Accuracy]: 0.7695,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1475:  99%|▉| 1475/1495 [08:32<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the signs clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?
A. vehicles
B. characters
C. sky
D. grassland
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, which object is emphasized in the center?
A. vehicles
B. characters
C. sky
D. grassland
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. vehicles\nB. characters\nC. sky\nD. grassland\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7695,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1475:  99%|▉| 1476/1495 [08:33<00
[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: vehicles, , [Prog]: 1476:  99%|▉| 1476/1495 [08
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>In image composition, which object is emphasized in the center?\nA. vehicles\nB. characters\nC. sky\nD. grassland\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of tennis player in this image?
A. Motion blur
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of tennis player in this image?
A. Motion blur
B. Noise
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of tennis player in this image?\nA. Motion blur\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1875], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7696,[Response]: A.<|endoftext|>, [Correct Ans]: vehicles, , [Prog]: 1476:  99%|▉| 1477/1495 [08
[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1477:  99%|▉| 1477/1495 
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the main distortion of tennis player in this image?\nA. Motion blur\nB. Noise\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?
A. Noise
B. Motion blur
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the worst distortion in this picture?
A. Noise
B. Motion blur
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What's the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7698,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1477:  99%|▉| 1478/1495 
[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1478:  99%|▉| 1478/1495 [08:33
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What's the worst distortion in this picture?\nA. Noise\nB. Motion blur\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?
A. Noise
B. Underexposure
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion of this picture?
A. Noise
B. Underexposure
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion of this picture?\nA. Noise\nB. Underexposure\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1478:  99%|▉| 1479/1495 [08:34
[Running Accuracy]: 0.7701,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1479:  99%|▉| 1479/1495
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion of this picture?\nA. Noise\nB. Underexposure\nC. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of this image?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Acceptable\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7701,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1479:  99%|▉| 1480/1495
[Running Accuracy]: 0.7696,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1480:  99%|▉| 1480/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the overall clarity of this image?\nA. Acceptable\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color with the highest saturation in the image?
A. Purple
B. Yellow
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color with the highest saturation in the image?
A. Purple
B. Yellow
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the color with the highest saturation in the image?\nA. Purple\nB. Yellow\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7696,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1480:  99%|▉| 1481/1495 [
[Running Accuracy]: 0.7698,[Response]: C.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1481:  99%|▉| 1481/1495 [08:35<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the color with the highest saturation in the image?\nA. Purple\nB. Yellow\nC. Red\nD. Blue\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the tree in the middle of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the tree in the middle of the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the tree in the middle of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7698,[Response]: C.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1481:  99%|▉| 1482/1495 [08:35<0
[Running Accuracy]: 0.7699,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1482:  99%|▉| 1482/1495 [08:35<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the clarity of the tree in the middle of the image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the noise in this image?
A. No noise
B. Severe noise
C. Weak noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the noise in this image?
A. No noise
B. Severe noise
C. Weak noise
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the noise in this image?\nA. No noise\nB. Severe noise\nC. Weak noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0938], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7699,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1482:  99%|▉| 1483/1495 [08:36<
[Running Accuracy]: 0.7694,[Response]: B.<|endoftext|>, [Correct Ans]: Weak noise, , [Prog]: 1483:  99%|▉| 1483/1495 [
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How severe is the noise in this image?\nA. No noise\nB. Severe noise\nC. Weak noise\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?
A. Noise
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this picture?
A. Noise
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7694,[Response]: B.<|endoftext|>, [Correct Ans]: Weak noise, , [Prog]: 1483:  99%|▉| 1484/1495 [
[Running Accuracy]: 0.7695,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1484:  99%|▉| 1484/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the worst distortion in this picture?\nA. Noise\nB. Out of focus\nC. Underexposure\nD. Motion blur\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the calender clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters on the calender clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters on the calender clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.8750], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7695,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1484:  99%|▉| 1485/149
[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1485:  99%|▉| 1485/1495 [08:37<00
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Are the characters on the calender clear in this picture?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clarity of the people on the street in this image?
A. Acceptable
B. High
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clarity of the people on the street in this image?
A. Acceptable
B. High
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["What is the clarity of the people on the street in this image?\nA. Acceptable\nB. High\nC. Poor\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7697,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1485:  99%|▉| 1486/1495 [08:38<00
[Running Accuracy]: 0.7699,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1486:  99%|▉| 1486/1495 [08:38<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the clarity of the people on the street in this image?\nA. Acceptable\nB. High\nC. Poor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography effects were applied to the image?
A. Bokeh
B. Shallow depth of field
C. Motion blur
D. Black and white filter
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What photography effects were applied to the image?
A. Bokeh
B. Shallow depth of field
C. Motion blur
D. Black and white filter
Answer with the option's letter from the given choices directly.

prompts: [["What photography effects were applied to the image?\nA. Bokeh\nB. Shallow depth of field\nC. Motion blur\nD. Black and white filter\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7699,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1486:  99%|▉| 1487/1495 [08:38<
[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Bokeh, , [Prog]: 1487:  99%|▉| 1487/1495 [08:38
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What photography effects were applied to the image?\nA. Bokeh\nB. Shallow depth of field\nC. Motion blur\nD. Black and white filter\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a dark visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark visual impression?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7700,[Response]: A.<|endoftext|>, [Correct Ans]: Bokeh, , [Prog]: 1487: 100%|▉| 1488/1495 [08:39
[Running Accuracy]: 0.7702,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1488: 100%|▉| 1488/1495 [08:39<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Does this image give a dark visual impression?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?
A. Vivid
B. Faded
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the image?
A. Vivid
B. Faded
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the image?\nA. Vivid\nB. Faded\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9688], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7702,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1488: 100%|▉| 1489/1495 [08:39<0
[Running Accuracy]: 0.7696,[Response]: C.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 1489: 100%|▉| 1489/1495 [08:39
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the color of the image?\nA. Vivid\nB. Faded\nC. Medium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?
A. Fresh
B. Bright
C. Dark
D. Joyful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual impression does the image give?
A. Fresh
B. Bright
C. Dark
D. Joyful
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does the image give?\nA. Fresh\nB. Bright\nC. Dark\nD. Joyful\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.7696,[Response]: C.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 1489: 100%|▉| 1490/1495 [08:39
[Running Accuracy]: 0.7698,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1490: 100%|▉| 1490/1495 [08:39<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What kind of visual impression does the image give?\nA. Fresh\nB. Bright\nC. Dark\nD. Joyful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9531], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7698,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1490: 100%|▉| 1491/1495 [08:40<
[Running Accuracy]: 0.7700,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1491: 100%|▉| 1491/1495 [08:40<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How is the sharpness of this image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus of the pizza in this image?
A. Medium
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus of the pizza in this image?
A. Medium
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus of the pizza in this image?\nA. Medium\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1250], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7700,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1491: 100%|▉| 1492/1495 [08:40<0
[Running Accuracy]: 0.7701,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1492: 100%|▉| 1492/1495 [08:40<
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>How's the focus of the pizza in this image?\nA. Medium\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall dominant color tone of the image?
A. White
B. Red
C. Green
D. Purple
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall dominant color tone of the image?
A. White
B. Red
C. Green
D. Purple
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall dominant color tone of the image?\nA. White\nB. Red\nC. Green\nD. Purple\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3594], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 D.

[Running Accuracy]: 0.7701,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1492: 100%|▉| 1493/1495 [08:40<
[Running Accuracy]: 0.7703,[Response]: D.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 1493: 100%|▉| 1493/1495 [08:4
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the overall dominant color tone of the image?\nA. White\nB. Red\nC. Green\nD. Purple\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject popcorn highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject popcorn highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject popcorn highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7812], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.7703,[Response]: D.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 1493: 100%|▉| 1494/1495 [08:4
[Running Accuracy]: 0.7704,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1494: 100%|▉| 1494/1495 [08:41<0
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the main subject popcorn highlighted?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?
A. Underexposure
B. Noise
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following quality issues does not exist in this image?
A. Underexposure
B. Noise
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does not exist in this image?\nA. Underexposure\nB. Noise\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7704,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1494: 100%|█| 1495/1495 [08:41<0
[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1495: 100%|█| 1495/149
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which of the following quality issues does not exist in this image?\nA. Underexposure\nB. Noise\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 


[Running Accuracy]: 0.7706,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1495: 100%|█| 1495/149