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 [01:37<01:37, 97.79s/it]
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████| 2/2 [02:04<00:00, 56.22s/it]
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████| 2/2 [02:04<00:00, 62.45s/it]
Loading pretrained qformer weights...
load vlm_att_encoder from pretrained <All keys matched successfully>
load vlm_att_ln from pretrained <All keys matched successfully>
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_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 lighting of this building?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this building?
A. High
B. Low
C. Medium
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 lighting of this building?\nA. High\nB. Low\nC. Medium\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.

  0%|                                                                                                        | 1/1495 [00:01<31:01,  1.25s/it]
[Running Accuracy]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1:   0%|               | 1/1495 [00:01<31:01,  1.25s/it]
 {'prompt': "A chat between a curious 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 building?\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 kind of distortion degrades the quality of the image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Compression Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion degrades the quality of the image?
A. Underexposure
B. Motion Blur
C. Overexposure
D. Compression Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion degrades the quality of the image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\nD. Compression Artifacts\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]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1:   0%|               | 2/1495 [00:01<18:02,  1.38it/s]
[Running Accuracy]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 2:   0%|       | 2/1495 [00:01<18:02,  1.38it/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>What kind of distortion degrades the quality of the image?\nA. Underexposure\nB. Motion Blur\nC. Overexposure\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>Are the flowers 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 flowers in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers in focus in this picture?\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]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 2:   0%|       | 3/1495 [00:01<13:32,  1.84it/s]
[Running Accuracy]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 3:   0%|               | 3/1495 [00:01<13:32,  1.84it/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>Are the flowers in focus 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>Are the skiers in the image too dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the skiers in the image too dark?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the skiers in the image too dark?\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]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 3:   0%|               | 4/1495 [00:02<11:15,  2.21it/s]
[Running Accuracy]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 4:   0%|               | 4/1495 [00:02<11:15,  2.21it/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>Are the skiers in the 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 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([-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]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 4:   0%|               | 5/1495 [00:02<10:18,  2.41it/s]
[Running Accuracy]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 5:   0%|               | 5/1495 [00:02<10:18,  2.41it/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>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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 schoolbus?
A. Vivid
B. Medium
C. Faded
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the schoolbus?
A. Vivid
B. Medium
C. Faded
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the schoolbus?\nA. Vivid\nB. Medium\nC. Faded\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]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 5:   0%|               | 6/1495 [00:02<09:43,  2.55it/s]
[Running Accuracy]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Vivid, , [Prog]: 6:   0%|             | 6/1495 [00:02<09:43,  2.55it/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 color of the schoolbus?\nA. Vivid\nB. Medium\nC. 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>Which kind of image quality problem 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 kind of image quality problem 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 kind of image quality problem 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([-31.2500], 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]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Vivid, , [Prog]: 6:   0%|             | 7/1495 [00:03<09:10,  2.70it/s]
[Running Accuracy]: 1.0000,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 7:   0%|     | 7/1495 [00:03<09:10,  2.70it/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>Which kind of image quality problem 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>Which part of the image is the clearest?
A. The woman's body
B. The woman's face
C. The environment behind the woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the clearest?
A. The woman's body
B. The woman's face
C. The environment behind the woman
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the clearest?\nA. The woman's body\nB. The woman's face\nC. The environment behind the woman\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]: 1.0000,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 7:   1%|     | 8/1495 [00:03<08:57,  2.77it/s]
[Running Accuracy]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: The woman's face, , [Prog]: 8:   1%|  | 8/1495 [00:03<08:57,  2.77it/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>Which part of the image is the clearest?\nA. The woman's body\nB. The woman's face\nC. The environment behind the woman\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 flowers in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting of the flowers in this image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting of the flowers in this image?\nA. Dark\nB. Medium\nC. Bright\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]: 1.0000,[Response]: B.<|endoftext|>, [Correct Ans]: The woman's face, , [Prog]: 8:   1%|  | 9/1495 [00:03<08:35,  2.88it/s]
[Running Accuracy]: 1.0000,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 9:   1%|            | 9/1495 [00:03<08:35,  2.88it/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>What do you think of the lighting of the flowers 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>Which person in the image has the most vibrant colors?
A. The woman in the bottom right corner of the image
B. The person in the bottom left corner of the image
C. The person in the lower part of the image
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which person in the image has the most vibrant colors?
A. The woman in the bottom right corner of the image
B. The person in the bottom left corner of the image
C. The person in the lower part of the image
Answer with the option's letter from the given choices directly.

prompts: [["Which person in the image has the most vibrant colors?\nA. The woman in the bottom right corner of the image\nB. The person in the bottom left corner of the image\nC. The person in the lower part of the image\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]: 1.0000,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 9:   1%|           | 10/1495 [00:04<08:35,  2.88it/s]
[Running Accuracy]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: The woman in the bottom right corner of the image, , [Prog]: 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>Which person in the image has the most vibrant colors?\nA. The woman in the bottom right corner of the image\nB. The person in the bottom left corner of the image\nC. The person in the lower part 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>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([-31.3594], 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]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: The woman in the bottom right corner of the image, , [Prog]: 10:   1%| 
[Running Accuracy]: 1.0000,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 11:   1%|        | 11/1495 [00:04<08:19,  2.97it/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 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 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([-31.1250], 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]: 1.0000,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 11:   1%|        | 12/1495 [00:04<08:07,  3.04it/s]
[Running Accuracy]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 12:   1%|             | 12/1495 [00:04<08:07,  3.04it/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>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>Which part of this image is severely overexposed?
A. The bottom part
B. Both
C. None
D. The top part
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is severely overexposed?
A. The bottom part
B. Both
C. None
D. The top part
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is severely overexposed?\nA. The bottom part\nB. Both\nC. None\nD. The top part\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]: 1.0000,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 12:   1%|             | 13/1495 [00:05<10:03,  2.45it/s]
[Running Accuracy]: 0.9231,[Response]: B.<|endoftext|>, [Correct Ans]: The bottom part, , [Prog]: 13:   1%| | 13/1495 [00:05<10:03,  2.45it/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>Which part of this image is severely overexposed?\nA. The bottom part\nB. Both\nC. None\nD. The top 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>Which object in this image is affected by slight motion blur?
A. cabinet
B. sofa
C. painting
D. woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is affected by slight motion blur?
A. cabinet
B. sofa
C. painting
D. woman
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is affected by slight motion blur?\nA. cabinet\nB. sofa\nC. painting\nD. woman\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]: 0.9231,[Response]: B.<|endoftext|>, [Correct Ans]: The bottom part, , [Prog]: 13:   1%| | 14/1495 [00:05<09:21,  2.64it/s]
[Running Accuracy]: 0.9286,[Response]: D.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 14:   1%|           | 14/1495 [00:05<09:21,  2.64it/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>Which object in this image is affected by slight motion blur?\nA. cabinet\nB. sofa\nC. painting\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>Is this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture in focus?\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]: 0.9286,[Response]: D.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 14:   1%|           | 15/1495 [00:06<08:47,  2.80it/s]
[Running Accuracy]: 0.9333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 15:   1%|▏             | 15/1495 [00:06<08:47,  2.80it/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>Is this picture 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 rope in the image clear?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the rope in the image clear?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.

prompts: [["Is the rope in the image clear?\nA. Clear\nB. Not clear\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]: 0.9333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 15:   1%|▏             | 16/1495 [00:06<08:39,  2.84it/s]
[Running Accuracy]: 0.9375,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 16:   1%|           | 16/1495 [00:06<08:39,  2.84it/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>Is the rope in the image clear?\nA. Clear\nB. Not 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>Are the students clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the students clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the students clear in this 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]: 0.9375,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 16:   1%|▏          | 17/1495 [00:06<08:33,  2.88it/s]
[Running Accuracy]: 0.8824,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 17:   1%|▏             | 17/1495 [00:06<08:33,  2.88it/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>Are the students clear 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 the humans in the middle of the image?
A. Noise
B. Blur
C. Low contrast
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the humans in the middle of the image?
A. Noise
B. Blur
C. Low contrast
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the humans in the middle of the image?\nA. Noise\nB. Blur\nC. Low contrast\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]: 0.8824,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 17:   1%|▏             | 18/1495 [00:07<12:05,  2.04it/s]
[Running Accuracy]: 0.8889,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 18:   1%|▏           | 18/1495 [00:07<12:05,  2.04it/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>What is the main distortion of the humans in the middle of the image?\nA. Noise\nB. 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 color 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 color 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 color saturation of the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2031], 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]: 0.8889,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 18:   1%|▏           | 19/1495 [00:07<10:44,  2.29it/s]
[Running Accuracy]: 0.8947,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 19:   1%|▏           | 19/1495 [00:07<10:44,  2.29it/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 color 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>Which is the main distortion in this image?
A. Underexposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the main distortion in this image?
A. Underexposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which is the main distortion in this image?\nA. Underexposure\nB. Blur\nC. Noise\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]: 0.8947,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 19:   1%|▏           | 20/1495 [00:08<11:02,  2.23it/s]
[Running Accuracy]: 0.9000,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 20:   1%|▏           | 20/1495 [00:08<11:02,  2.23it/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>Which is the main distortion in this image?\nA. Underexposure\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>How is the symmetry of this image?
A. Vertically symmetrical
B. Horizontally symmetrical
C. Not symmetrical
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the symmetry of this image?
A. Vertically symmetrical
B. Horizontally symmetrical
C. Not symmetrical
Answer with the option's letter from the given choices directly.

prompts: [["How is the symmetry of this image?\nA. Vertically symmetrical\nB. Horizontally symmetrical\nC. Not symmetrical\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]: 0.9000,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 20:   1%|▏           | 21/1495 [00:08<09:58,  2.46it/s]
[Running Accuracy]: 0.9048,[Response]: B.<|endoftext|>, [Correct Ans]: Horizontally symmetrical, , [Prog]: 21:   1%| | 21/1495 [00:08<09:58,  
 {'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 symmetry of this image?\nA. Vertically symmetrical\nB. Horizontally symmetrical\nC. Not symmetrical\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.0312], 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]: 0.9048,[Response]: B.<|endoftext|>, [Correct Ans]: Horizontally symmetrical, , [Prog]: 21:   1%| | 22/1495 [00:09<09:34,  
[Running Accuracy]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 22:   1%|▏            | 22/1495 [00:09<09:34,  2.56it/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>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>Where is the focus of this picture?
A. Background
B. People
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Background
B. People
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Background\nB. People\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]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 22:   2%|▏            | 23/1495 [00:09<09:24,  2.61it/s]
[Running Accuracy]: 0.8696,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 23:   2%|▏         | 23/1495 [00:09<09:24,  2.61it/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>Where is the focus of this picture?\nA. Background\nB. People\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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([-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]: 0.8696,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 23:   2%|▏         | 24/1495 [00:09<09:04,  2.70it/s]
[Running Accuracy]: 0.8750,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 24:   2%|▏             | 24/1495 [00:09<09:04,  2.70it/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>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 clarity of 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 clarity of the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Good\nB. Moderate\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]: 0.8750,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 24:   2%|▏             | 25/1495 [00:10<09:02,  2.71it/s]
[Running Accuracy]: 0.8800,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 25:   2%|▏       | 25/1495 [00:10<09:02,  2.71it/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 clarity of the image?\nA. Good\nB. Moderate\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>Are the textures clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the textures clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the textures clear in this image?\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])
 B.

[Running Accuracy]: 0.8800,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 25:   2%|▏       | 26/1495 [00:10<09:01,  2.71it/s]
[Running Accuracy]: 0.8846,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 26:   2%|▏             | 26/1495 [00:10<09:01,  2.71it/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>Are the textures 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>What are the overall distortion level of the image?
A. Severely distorted
B. Moderately distorted
C. Not distorted
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are the overall distortion level of the image?
A. Severely distorted
B. Moderately distorted
C. Not distorted
Answer with the option's letter from the given choices directly.

prompts: [["What are the overall distortion level of the image?\nA. Severely distorted\nB. Moderately distorted\nC. Not distorted\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]: 0.8846,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 26:   2%|▎             | 27/1495 [00:11<10:33,  2.32it/s]
[Running Accuracy]: 0.8889,[Response]: A.<|endoftext|>, [Correct Ans]: Severely distorted, , [Prog]: 27:   2%| | 27/1495 [00:11<10:33,  2.32it
 {'prompt': "A chat between 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 overall distortion level of the image?\nA. Severely distorted\nB. Moderately distorted\nC. Not distorted\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 baby's clothes?
A. Acceptable
B. Annoying
C. Pleasing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the baby's clothes?
A. Acceptable
B. Annoying
C. Pleasing
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the baby's clothes?\nA. Acceptable\nB. Annoying\nC. Pleasing\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]: 0.8889,[Response]: A.<|endoftext|>, [Correct Ans]: Severely distorted, , [Prog]: 27:   2%| | 28/1495 [00:11<09:50,  2.49it
[Running Accuracy]: 0.8929,[Response]: C.<|endoftext|>, [Correct Ans]: Pleasing, , [Prog]: 28:   2%|▏       | 28/1495 [00:11<09:50,  2.49it/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 color of the baby's clothes?\nA. Acceptable\nB. Annoying\nC. Pleasing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["Is the face of the man clear?\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]: 0.8929,[Response]: C.<|endoftext|>, [Correct Ans]: Pleasing, , [Prog]: 28:   2%|▏       | 29/1495 [00:11<09:19,  2.62it/s]
[Running Accuracy]: 0.8966,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 29:   2%|▎            | 29/1495 [00:11<09:19,  2.62it/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>Is the face of the man 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 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([-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]: 0.8966,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 29:   2%|▎            | 30/1495 [00:12<08:57,  2.72it/s]
[Running Accuracy]: 0.9000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 30:   2%|▎             | 30/1495 [00:12<08:57,  2.72it/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>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>What is the major distortion of the bed 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 major distortion of the bed 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 major distortion of the bed in this image?\nA. Blur\nB. Over-exposure\nC. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], 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]: 0.9000,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 30:   2%|▎             | 31/1495 [00:12<08:30,  2.87it/s]
[Running Accuracy]: 0.9032,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 31:   2%|▏          | 31/1495 [00:12<08:30,  2.87it/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>What is the major distortion of the bed in this image?\nA. Blur\nB. Over-exposure\nC. 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. 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 is the worst distortion 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 is the worst distortion 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([-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]: 0.9032,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 31:   2%|▏          | 32/1495 [00:12<08:25,  2.89it/s]
[Running Accuracy]: 0.9062,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 32:   2%|    | 32/1495 [00:12<08:25,  2.89it/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>What is the worst distortion 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': 'A.<|endoftext|>'} 

prompt A chat between 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([-30.8750], 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]: 0.9062,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 32:   2%|    | 33/1495 [00:13<08:10,  2.98it/s]
[Running Accuracy]: 0.9091,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 33:   2%|▎           | 33/1495 [00:13<08:10,  2.98it/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 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>Does this image suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image suffer from over-exposure?\nA. Yes\nB. No\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])
 B.

[Running Accuracy]: 0.9091,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 33:   2%|▎           | 34/1495 [00:13<08:50,  2.75it/s]
[Running Accuracy]: 0.9118,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 34:   2%|▎             | 34/1495 [00:13<08:50,  2.75it/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>Does this image suffer from over-exposure?\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 distortion can be found on the wall in the right?
A. Underexposure
B. Motion blur
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion can be found on the wall in the right?
A. Underexposure
B. Motion blur
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion can be found on the wall in the right?\nA. Underexposure\nB. Motion blur\nC. Overexposure\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]: 0.9118,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 34:   2%|▎             | 35/1495 [00:13<08:25,  2.89it/s]
[Running Accuracy]: 0.9143,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 35:   2%|    | 35/1495 [00:13<08:25,  2.89it/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>What distortion can be found on the wall in the right?\nA. Underexposure\nB. Motion blur\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>What is the most apparent distortion of the ceiling in 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 the ceiling in 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 the ceiling in this image?\nA. Over-exposure\nB. Noise\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])
 B.

[Running Accuracy]: 0.9143,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 35:   2%|    | 36/1495 [00:14<10:19,  2.35it/s]
[Running Accuracy]: 0.9167,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 36:   2%|▎          | 36/1495 [00:14<10:19,  2.35it/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>What is the most apparent distortion of the ceiling in 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>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([-30.8750], 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]: 0.9167,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 36:   2%|▎          | 37/1495 [00:14<09:32,  2.55it/s]
[Running Accuracy]: 0.9189,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 37:   2%|▎            | 37/1495 [00:14<09:32,  2.55it/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>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>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([-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]: 0.9189,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 37:   3%|▎            | 38/1495 [00:14<08:42,  2.79it/s]
[Running Accuracy]: 0.9211,[Response]: B<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 38:   3%|▎            | 38/1495 [00:14<08:42,  2.79it/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 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>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([-31.4062], 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]: 0.9211,[Response]: B<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 38:   3%|▎            | 39/1495 [00:15<10:22,  2.34it/s]
[Running Accuracy]: 0.9231,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 39:   3%|▎            | 39/1495 [00:15<10:22,  2.34it/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>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 bright is this picture?
A. Dull
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dull
B. Normal
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dull\nB. Normal\nC. Bright\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]: 0.9231,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 39:   3%|▎            | 40/1495 [00:16<10:52,  2.23it/s]
[Running Accuracy]: 0.9000,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 40:   3%|▎         | 40/1495 [00:16<10:52,  2.23it/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 bright is this picture?\nA. Dull\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>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([-31.1094], 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]: 0.9000,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 40:   3%|▎         | 41/1495 [00:16<10:01,  2.42it/s]
[Running Accuracy]: 0.9024,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 41:   3%|▍             | 41/1495 [00:16<10:01,  2.42it/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>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>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([-31.5000], 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]: 0.9024,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 41:   3%|▍             | 42/1495 [00:16<09:20,  2.59it/s]
[Running Accuracy]: 0.9048,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 42:   3%|▎            | 42/1495 [00:16<09:20,  2.59it/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>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>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([-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]: 0.9048,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 42:   3%|▎            | 43/1495 [00:17<08:56,  2.71it/s]
[Running Accuracy]: 0.9070,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 43:   3%|▍             | 43/1495 [00:17<08:56,  2.71it/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>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': 'B.<|endoftext|>'} 

prompt A chat between 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. Clear
B. Average
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image?
A. Clear
B. Average
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Clear\nB. Average\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]: 0.9070,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 43:   3%|▍             | 44/1495 [00:17<08:32,  2.83it/s]
[Running Accuracy]: 0.9091,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 44:   3%|▎          | 44/1495 [00:17<08:32,  2.83it/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 clear is the image?\nA. Clear\nB. Average\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 clear is the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear is 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])
 A.

[Running Accuracy]: 0.9091,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 44:   3%|▎          | 45/1495 [00:17<08:20,  2.90it/s]
[Running Accuracy]: 0.8889,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 45:   3%|▎           | 45/1495 [00:17<08:20,  2.90it/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 clear is 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>How is the contrast level 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 contrast level of this 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 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]: 0.8889,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 45:   3%|▎           | 46/1495 [00:17<07:59,  3.02it/s]
[Running Accuracy]: 0.8913,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 46:   3%|▍            | 46/1495 [00:17<07:59,  3.02it/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 contrast level 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 overall 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 overall 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 overall clarity of this image?\nA. Medium\nB. Low\nC. High\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]: 0.8913,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 46:   3%|▍            | 47/1495 [00:18<09:44,  2.48it/s]
[Running Accuracy]: 0.8936,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 47:   3%|▍           | 47/1495 [00:18<09:44,  2.48it/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 overall clarity 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 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([-31.4531], 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]: 0.8936,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 47:   3%|▍           | 48/1495 [00:18<09:14,  2.61it/s]
[Running Accuracy]: 0.8958,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 48:   3%|▍             | 48/1495 [00:18<09:14,  2.61it/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>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>What's the worst distortion in this picture?
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's the worst distortion in this picture?
A. Overexposure
B. Underexposure
C. Noise
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. Overexposure\nB. Underexposure\nC. Noise\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])
 D.

[Running Accuracy]: 0.8958,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 48:   3%|▍             | 49/1495 [00:19<11:03,  2.18it/s]
[Running Accuracy]: 0.8980,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 49:   3%|▏   | 49/1495 [00:19<11:03,  2.18it/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>What's the worst distortion in this picture?\nA. Overexposure\nB. Underexposure\nC. Noise\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 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([-31.2969], 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]: 0.8980,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 49:   3%|▏   | 50/1495 [00:19<10:18,  2.34it/s]
[Running Accuracy]: 0.9000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 50:   3%|▍            | 50/1495 [00:19<10:18,  2.34it/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>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>What is the main distortion with the image?
A. Overexposure
B. Motion blur
C. Compression artifacts
D. Backlighting
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion with the image?
A. Overexposure
B. Motion blur
C. Compression artifacts
D. Backlighting
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion with the image?\nA. Overexposure\nB. Motion blur\nC. Compression artifacts\nD. Backlighting\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])
 D.

[Running Accuracy]: 0.9000,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 50:   3%|▍            | 51/1495 [00:20<09:36,  2.51it/s]
[Running Accuracy]: 0.9020,[Response]: D.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 51:   3%|▏   | 51/1495 [00:20<09:36,  2.51it/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>What is the main distortion with the image?\nA. Overexposure\nB. Motion blur\nC. Compression artifacts\nD. Backlighting\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 emphasized in the center of this image?
A. Bowl
B. Window
C. Panda
D. Table
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. Bowl
B. Window
C. Panda
D. Table
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. Bowl\nB. Window\nC. Panda\nD. Table\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]: 0.9020,[Response]: D.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 51:   3%|▏   | 52/1495 [00:20<08:47,  2.73it/s]
[Running Accuracy]: 0.9038,[Response]: C.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 52:   3%|▍          | 52/1495 [00:20<08:47,  2.73it/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>Which object is emphasized in the center of this image?\nA. Bowl\nB. Window\nC. Panda\nD. Table\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 this image is relatively darker?
A. The top area
B. The central area
C. The bottom area
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which area in this image is relatively darker?
A. The top area
B. The central area
C. The bottom area
Answer with the option's letter from the given choices directly.

prompts: [["Which area in this image is relatively darker?\nA. The top area\nB. The central area\nC. The bottom area\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]: 0.9038,[Response]: C.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 52:   4%|▍          | 53/1495 [00:21<10:20,  2.32it/s]
[Running Accuracy]: 0.8868,[Response]: C.<|endoftext|>, [Correct Ans]: The top area, , [Prog]: 53:   4%|▏   | 53/1495 [00:21<10:20,  2.32it/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>Which area in this image is relatively darker?\nA. The top area\nB. The central area\nC. The bottom area\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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([-31.3281], 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]: 0.8868,[Response]: C.<|endoftext|>, [Correct Ans]: The top area, , [Prog]: 53:   4%|▏   | 54/1495 [00:21<09:23,  2.56it/s]
[Running Accuracy]: 0.8704,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 54:   4%|▍           | 54/1495 [00:21<09:23,  2.56it/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 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>How clear is the man in black clothes in the image?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the man in black clothes in the image?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the man in black clothes in the image?\nA. Clear\nB. Blurry\nC. Average\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]: 0.8704,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 54:   4%|▍           | 55/1495 [00:21<08:52,  2.70it/s]
[Running Accuracy]: 0.8545,[Response]: A.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 55:   4%|▎        | 55/1495 [00:21<08:52,  2.70it/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 clear is the man in black clothes in the image?\nA. Clear\nB. Blurry\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 chairs in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the chairs in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the chairs in this picture 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])
 A.

[Running Accuracy]: 0.8545,[Response]: A.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 55:   4%|▎        | 56/1495 [00:22<11:10,  2.15it/s]
[Running Accuracy]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 56:   4%|▌             | 56/1495 [00:22<11:10,  2.15it/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>Are the chairs 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 in the image is the darkest?
A. table
B. woman
C. vegetables
D. tableware
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the darkest?
A. table
B. woman
C. vegetables
D. tableware
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the darkest?\nA. table\nB. woman\nC. vegetables\nD. tableware\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]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 56:   4%|▌             | 57/1495 [00:22<10:09,  2.36it/s]
[Running Accuracy]: 0.8596,[Response]: B.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 57:   4%|▍          | 57/1495 [00:22<10:09,  2.36it/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>Which object in the image is the darkest?\nA. table\nB. woman\nC. vegetables\nD. tableware\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 sky in the image suffer from?
A. Overexposure
B. Noise
C. Underexposure
D. Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does the sky in the image suffer from?
A. Overexposure
B. Noise
C. Underexposure
D. Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does the sky in the image suffer from?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. Artifacts\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]: 0.8596,[Response]: B.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 57:   4%|▍          | 58/1495 [00:23<11:24,  2.10it/s]
[Running Accuracy]: 0.8621,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 58:   4%|▏   | 58/1495 [00:23<11:24,  2.10it/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>What distortion does the sky in the image suffer from?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. 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 color saturation 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 color saturation of the image?
A. Good
B. Poor
C. Moderate
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. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.8125], 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]: 0.8621,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 58:   4%|▏   | 59/1495 [00:23<10:14,  2.34it/s]
[Running Accuracy]: 0.8475,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 59:   4%|▍           | 59/1495 [00:23<10:14,  2.34it/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 color saturation of the image?\nA. Good\nB. Poor\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 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([-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]: 0.8475,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 59:   4%|▍           | 60/1495 [00:24<11:31,  2.07it/s]
[Running Accuracy]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 60:   4%|▌            | 60/1495 [00:24<11:31,  2.07it/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>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': 'B.<|endoftext|>'} 

prompt A chat 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([-31.5156], 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]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 60:   4%|▌            | 61/1495 [00:24<10:32,  2.27it/s]
[Running Accuracy]: 0.8525,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 61:   4%|▌            | 61/1495 [00:24<10:32,  2.27it/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>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>How bright is this picture?
A. Dim
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dim
B. Bright
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dim\nB. Bright\nC. Normal\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]: 0.8525,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 61:   4%|▌            | 62/1495 [00:25<11:22,  2.10it/s]
[Running Accuracy]: 0.8548,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 62:   4%|▍         | 62/1495 [00:25<11:22,  2.10it/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 bright is this picture?\nA. Dim\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>What is the brightest object in this picture?
A. Glasses
B. Table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest object in this picture?
A. Glasses
B. Table
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest object in this picture?\nA. Glasses\nB. Table\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]: 0.8548,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 62:   4%|▍         | 63/1495 [00:25<10:18,  2.31it/s]
[Running Accuracy]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: Glasses, , [Prog]: 63:   4%|▍        | 63/1495 [00:25<10:18,  2.31it/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>What is the brightest object in this picture?\nA. Glasses\nB. 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>What is the main color tone of the image?
A. Brown
B. Gray
C. Green
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. Brown
B. Gray
C. Green
D. White
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Brown\nB. Gray\nC. Green\nD. White\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]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: Glasses, , [Prog]: 63:   4%|▍        | 64/1495 [00:25<09:27,  2.52it/s]
[Running Accuracy]: 0.8594,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 64:   4%|▍          | 64/1495 [00:25<09:27,  2.52it/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>What is the main color tone of the image?\nA. Brown\nB. Gray\nC. Green\nD. White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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([-31.3281], 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]: 0.8594,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 64:   4%|▍          | 65/1495 [00:26<08:47,  2.71it/s]
[Running Accuracy]: 0.8615,[Response]: A.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 65:   4%|▍         | 65/1495 [00:26<08:47,  2.71it/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 bright is this picture?\nA. Normal\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 motion blur of the humans in this image?
A. Strong
B. Medium
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the motion blur of the humans in this image?
A. Strong
B. Medium
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How is the motion blur of the humans in this image?\nA. Strong\nB. Medium\nC. Weak\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]: 0.8615,[Response]: A.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 65:   4%|▍         | 66/1495 [00:26<08:26,  2.82it/s]
[Running Accuracy]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 66:   4%|▍         | 66/1495 [00:26<08:26,  2.82it/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 motion blur of the humans in this image?\nA. Strong\nB. Medium\nC. Weak\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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([-31.3125], 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]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 66:   4%|▍         | 67/1495 [00:26<08:11,  2.90it/s]
[Running Accuracy]: 0.8507,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 67:   4%|▌            | 67/1495 [00:26<08:11,  2.90it/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>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 this image show contrast in its lighting?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image show contrast in its lighting?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image show contrast in its lighting?\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]: 0.8507,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 67:   5%|▌            | 68/1495 [00:27<08:26,  2.82it/s]
[Running Accuracy]: 0.8529,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 68:   5%|▌            | 68/1495 [00:27<08:26,  2.82it/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>Does this image show contrast in its lighting?\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. 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([-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]: 0.8529,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 68:   5%|▌            | 69/1495 [00:27<10:11,  2.33it/s]
[Running Accuracy]: 0.8551,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 69:   5%|▌          | 69/1495 [00:27<10:11,  2.33it/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 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>Is the color of the fruit 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 fruit 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 fruit in this image vivid?\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]: 0.8551,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 69:   5%|▌          | 70/1495 [00:28<09:18,  2.55it/s]
[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 70:   5%|▌            | 70/1495 [00:28<09:18,  2.55it/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>Is the color of the fruit in this image vivid?\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 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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.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]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 70:   5%|▌            | 71/1495 [00:28<08:45,  2.71it/s]
[Running Accuracy]: 0.8592,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 71:   5%|▌            | 71/1495 [00:28<08:45,  2.71it/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>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>How would you rate the clarity of the in this image?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the in this image?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the in this image?\nA. Low\nB. High\nC. Acceptable\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]: 0.8592,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 71:   5%|▋            | 72/1495 [00:28<08:19,  2.85it/s]
[Running Accuracy]: 0.8472,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 72:   5%|▎     | 72/1495 [00:28<08:19,  2.85it/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 would you rate the clarity of the in this image?\nA. Low\nB. High\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 athlete 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 clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the athlete clear in the image?\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]: 0.8472,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 72:   5%|▎     | 73/1495 [00:28<08:12,  2.89it/s]
[Running Accuracy]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 73:   5%|▋             | 73/1495 [00:28<08:12,  2.89it/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>Is the athlete 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>How is the lighting of the buildings?
A. Medium
B. High
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the buildings?
A. Medium
B. High
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the buildings?\nA. Medium\nB. High\nC. Dark\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]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 73:   5%|▋             | 74/1495 [00:29<10:07,  2.34it/s]
[Running Accuracy]: 0.8514,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 74:   5%|▌           | 74/1495 [00:29<10:07,  2.34it/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 lighting of the buildings?\nA. Medium\nB. High\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 exposure of the human in 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 the human in 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 the human in this image?\nA. Under-exposure\nB. Appropriate\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], 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]: 0.8514,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 74:   5%|▌           | 75/1495 [00:30<11:10,  2.12it/s]
[Running Accuracy]: 0.8533,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 75:   5%|  | 75/1495 [00:30<11:10,  2.12it/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 exposure of the human in this image?\nA. Under-exposure\nB. Appropriate\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 is emphasized in the center in the composition of the image?
A. mountain
B. grass
C. boat
D. tree
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center in the composition of the image?
A. mountain
B. grass
C. boat
D. tree
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center in the composition of the image?\nA. mountain\nB. grass\nC. boat\nD. tree\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]: 0.8533,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 75:   5%|  | 76/1495 [00:30<10:15,  2.31it/s]
[Running Accuracy]: 0.8553,[Response]: C.<|endoftext|>, [Correct Ans]: boat, , [Prog]: 76:   5%|▌           | 76/1495 [00:30<10:15,  2.31it/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>Which object is emphasized in the center in the composition of the image?\nA. mountain\nB. grass\nC. boat\nD. tree\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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?
A. Dark
B. Average
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the image?
A. Dark
B. Average
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the image?\nA. Dark\nB. Average\nC. Bright\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]: 0.8553,[Response]: C.<|endoftext|>, [Correct Ans]: boat, , [Prog]: 76:   5%|▌           | 77/1495 [00:31<11:06,  2.13it/s]
[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 77:   5%|▌         | 77/1495 [00:31<11:06,  2.13it/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 lighting condition of the image?\nA. Dark\nB. Average\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 most prominent color 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 most prominent color 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 most prominent color 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([-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]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 77:   5%|▌         | 78/1495 [00:31<10:04,  2.34it/s]
[Running Accuracy]: 0.8590,[Response]: C.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 78:   5%|▌         | 78/1495 [00:31<10:04,  2.34it/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>What is the most prominent color 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': 'C.<|endoftext|>'} 

prompt A chat between 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([-31.3125], 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]: 0.8590,[Response]: C.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 78:   5%|▌         | 79/1495 [00:31<09:13,  2.56it/s]
[Running Accuracy]: 0.8608,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 79:   5%|▋             | 79/1495 [00:31<09:13,  2.56it/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>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 problems exist in the image?
A. Motion blur
B. Backlighting
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Motion blur
B. Backlighting
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Motion blur\nB. Backlighting\nC. Underexposure\nD. Overexposure\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]: 0.8608,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 79:   5%|▋             | 80/1495 [00:32<08:47,  2.68it/s]
[Running Accuracy]: 0.8625,[Response]: B.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 80:   5%|▏   | 80/1495 [00:32<08:47,  2.68it/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>What problems exist in the image?\nA. Motion blur\nB. Backlighting\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 it a dark image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is it a dark image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is it a dark 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]: 0.8625,[Response]: B.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 80:   5%|▏   | 81/1495 [00:32<08:41,  2.71it/s]
[Running Accuracy]: 0.8642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 81:   5%|▋            | 81/1495 [00:32<08:41,  2.71it/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>Is it a dark 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 shot in real life?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image shot in real life?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image shot in real life?\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]: 0.8642,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 81:   5%|▋            | 82/1495 [00:32<08:22,  2.81it/s]
[Running Accuracy]: 0.8659,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 82:   5%|▊             | 82/1495 [00:32<08:22,  2.81it/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>Is the image shot in real life?\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. 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([-30.7812], 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]: 0.8659,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 82:   6%|▊             | 83/1495 [00:33<08:49,  2.67it/s]
[Running Accuracy]: 0.8675,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 83:   6%|▋            | 83/1495 [00:33<08:49,  2.67it/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>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>Is there any distortion issue in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any distortion issue in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any distortion issue 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])
 A.

[Running Accuracy]: 0.8675,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 83:   6%|▋            | 84/1495 [00:33<08:33,  2.75it/s]
[Running Accuracy]: 0.8690,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 84:   6%|▊             | 84/1495 [00:33<08:33,  2.75it/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>Is there any distortion 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 is the most apparent distortion for the humans in this image?
A. Under-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion for the humans in this image?
A. Under-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion for the humans in this image?\nA. Under-exposure\nB. Blur\nC. Noise\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]: 0.8690,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 84:   6%|▊             | 85/1495 [00:33<08:13,  2.86it/s]
[Running Accuracy]: 0.8706,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 85:   6%|  | 85/1495 [00:33<08:13,  2.86it/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>What is the most apparent distortion for the humans in this image?\nA. Under-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>To what extent is the vehicle blurred in the image?
A. Not blurred at all
B. Very blurry
C. Some blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the vehicle blurred in the image?
A. Not blurred at all
B. Very blurry
C. Some blur
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the vehicle blurred in the image?\nA. Not blurred at all\nB. Very blurry\nC. Some blur\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]: 0.8706,[Response]: A.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 85:   6%|  | 86/1495 [00:34<08:09,  2.88it/s]
[Running Accuracy]: 0.8605,[Response]: B.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 86:   6%|▍      | 86/1495 [00:34<08:09,  2.88it/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>To what extent is the vehicle blurred in the image?\nA. Not blurred at all\nB. Very blurry\nC. Some 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>What is the clearest object in the image?
A. Small wooden house
B. Person in green clothing
C. Race car
D. Person in purple clothing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Small wooden house
B. Person in green clothing
C. Race car
D. Person in purple clothing
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Small wooden house\nB. Person in green clothing\nC. Race car\nD. Person in purple clothing\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]: 0.8605,[Response]: B.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 86:   6%|▍      | 87/1495 [00:34<08:20,  2.81it/s]
[Running Accuracy]: 0.8621,[Response]: C.<|endoftext|>, [Correct Ans]: Race car, , [Prog]: 87:   6%|▍       | 87/1495 [00:34<08:20,  2.81it/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>What is the clearest object in the image?\nA. Small wooden house\nB. Person in green clothing\nC. Race car\nD. Person in purple clothing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 duck 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 duck 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 duck in the image?\nA. Clear\nB. Moderate\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]: 0.8621,[Response]: C.<|endoftext|>, [Correct Ans]: Race car, , [Prog]: 87:   6%|▍       | 88/1495 [00:34<08:28,  2.77it/s]
[Running Accuracy]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 88:   6%|▋          | 88/1495 [00:34<08:28,  2.77it/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 clear is the duck 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 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([-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]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 88:   6%|▋          | 89/1495 [00:35<08:25,  2.78it/s]
[Running Accuracy]: 0.8652,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 89:   6%|▌         | 89/1495 [00:35<08:25,  2.78it/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 quality of this picture?\nA. High\nB. Low\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>Is the cow clear in the image?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cow clear in the image?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.

prompts: [["Is the cow clear in the image?\nA. Clear\nB. Not clear\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]: 0.8652,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 89:   6%|▌         | 90/1495 [00:35<08:13,  2.85it/s]
[Running Accuracy]: 0.8667,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 90:   6%|▋          | 90/1495 [00:35<08:13,  2.85it/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>Is the cow clear in the image?\nA. Clear\nB. Not 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 subject emphasized in the center of this 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 this 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 this image composition?\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]: 0.8667,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 90:   6%|▋          | 91/1495 [00:35<07:58,  2.93it/s]
[Running Accuracy]: 0.8681,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 91:   6%|▊            | 91/1495 [00:35<07:58,  2.93it/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>Is the subject emphasized in the center of this 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 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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8681,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 91:   6%|▊            | 92/1495 [00:36<07:48,  2.99it/s]
[Running Accuracy]: 0.8696,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 92:   6%|▊            | 92/1495 [00:36<07:48,  2.99it/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>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>Which object in the image appears the brightest?
A. The flame on the table
B. The stone wall behind the figure
C. The stone table
D. The figure sitting behind the table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image appears the brightest?
A. The flame on the table
B. The stone wall behind the figure
C. The stone table
D. The figure sitting behind the table
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image appears the brightest?\nA. The flame on the table\nB. The stone wall behind the figure\nC. The stone table\nD. The figure sitting behind the table\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]: 0.8696,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 92:   6%|▊            | 93/1495 [00:36<07:45,  3.01it/s]
[Running Accuracy]: 0.8710,[Response]: A.<|endoftext|>, [Correct Ans]: The flame on the table, , [Prog]: 93:   6%| | 93/1495 [00:36<07:45,  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 the image appears the brightest?\nA. The flame on the table\nB. The stone wall behind the figure\nC. The stone table\nD. The figure sitting behind the 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>Which of the following quality issues does not exist in this image?
A. Noise
B. Overexposure
C. Underexposure
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 this image?
A. Noise
B. Overexposure
C. Underexposure
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 this image?\nA. Noise\nB. Overexposure\nC. Underexposure\nD. Out of focus\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]: 0.8710,[Response]: A.<|endoftext|>, [Correct Ans]: The flame on the table, , [Prog]: 93:   6%| | 94/1495 [00:36<07:41,  3.
[Running Accuracy]: 0.8617,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 94:   6%|▎   | 94/1495 [00:36<07:41,  3.04it/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>Which of the following quality issues does not exist in this image?\nA. Noise\nB. Overexposure\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>Would you say the composition in this photo 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 photo 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 photo is good?\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]: 0.8617,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 94:   6%|▎   | 95/1495 [00:37<07:34,  3.08it/s]
[Running Accuracy]: 0.8632,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 95:   6%|▉             | 95/1495 [00:37<07:34,  3.08it/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>Would you say the composition in this photo is 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>Does this image give a fresh 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 fresh visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a fresh visual impression?\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])
 B.

[Running Accuracy]: 0.8632,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 95:   6%|▉             | 96/1495 [00:37<07:49,  2.98it/s]
[Running Accuracy]: 0.8542,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 96:   6%|▉             | 96/1495 [00:37<07:49,  2.98it/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>Does this image give a fresh 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>Does this image give a sense of brightness?
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 brightness?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a sense of brightness?\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]: 0.8542,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 96:   6%|▉             | 97/1495 [00:37<07:41,  3.03it/s]
[Running Accuracy]: 0.8557,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 97:   6%|▉             | 97/1495 [00:37<07:41,  3.03it/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>Does this image give a sense of brightness?\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 composition does the image adopt?
A. Centered
B. Diagonal
C. Symmetrical
D. Pyramid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of composition does the image adopt?
A. Centered
B. Diagonal
C. Symmetrical
D. Pyramid
Answer with the option's letter from the given choices directly.

prompts: [["What kind of composition does the image adopt?\nA. Centered\nB. Diagonal\nC. Symmetrical\nD. Pyramid\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]: 0.8557,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 97:   7%|▉             | 98/1495 [00:38<07:36,  3.06it/s]
[Running Accuracy]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: Centered, , [Prog]: 98:   7%|▌       | 98/1495 [00:38<07:36,  3.06it/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>What kind of composition does the image adopt?\nA. Centered\nB. Diagonal\nC. Symmetrical\nD. Pyramid\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color saturated?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color saturated?\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]: 0.8571,[Response]: A.<|endoftext|>, [Correct Ans]: Centered, , [Prog]: 98:   7%|▌       | 99/1495 [00:38<07:24,  3.14it/s]
[Running Accuracy]: 0.8586,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 99:   7%|▊            | 99/1495 [00:38<07:24,  3.14it/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>Is the image color 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>Is the color of the small hanging object on the ceiling in this picture vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the small hanging object on the ceiling in this picture vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the small hanging object on the ceiling in this picture vibrant?\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]: 0.8586,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 99:   7%|▊           | 100/1495 [00:38<07:30,  3.10it/s]
[Running Accuracy]: 0.8600,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 100:   7%|▋          | 100/1495 [00:38<07:30,  3.10it/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>Is the color of the small hanging object on the ceiling 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>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([-31.3281], 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]: 0.8600,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 100:   7%|▋          | 101/1495 [00:39<07:59,  2.91it/s]
[Running Accuracy]: 0.8614,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 101:   7%|▋          | 101/1495 [00:39<07:59,  2.91it/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 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': 'C.<|endoftext|>'} 

prompt A chat 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([-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])
 A.

[Running Accuracy]: 0.8614,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 101:   7%|▊          | 102/1495 [00:39<07:41,  3.02it/s]
[Running Accuracy]: 0.8529,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 102:   7%|▊           | 102/1495 [00:39<07:41,  3.02it/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>Does this picture 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>Does this image look clean or noisy?
A. Noisy
B. Clean
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look clean or noisy?
A. Noisy
B. Clean
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look clean or noisy?\nA. Noisy\nB. Clean\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]: 0.8529,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 102:   7%|▊           | 103/1495 [00:39<07:32,  3.08it/s]
[Running Accuracy]: 0.8544,[Response]: A.<|endoftext|>, [Correct Ans]: Noisy, , [Prog]: 103:   7%|▌        | 103/1495 [00:39<07:32,  3.08it/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>Does this image look clean or noisy?\nA. Noisy\nB. Clean\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 tree in this image?
A. Weak
B. Acceptable
C. Strong
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the motion blur of the tree in this image?
A. Weak
B. Acceptable
C. Strong
Answer with the option's letter from the given choices directly.

prompts: [["How is the motion blur of the tree in this image?\nA. Weak\nB. Acceptable\nC. Strong\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]: 0.8544,[Response]: A.<|endoftext|>, [Correct Ans]: Noisy, , [Prog]: 103:   7%|▋        | 104/1495 [00:40<08:18,  2.79it/s]
[Running Accuracy]: 0.8558,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 104:   7%|▌       | 104/1495 [00:40<08:18,  2.79it/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 motion blur of the tree in this image?\nA. Weak\nB. Acceptable\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>What distortion occurs in this image?
A. Noise
B. Motion Blur
C. Out of Focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion occurs in this image?
A. Noise
B. Motion Blur
C. Out of Focus
Answer with the option's letter from the given choices directly.

prompts: [["What distortion occurs in this image?\nA. Noise\nB. Motion Blur\nC. Out of Focus\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]: 0.8558,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 104:   7%|▌       | 105/1495 [00:40<09:56,  2.33it/s]
[Running Accuracy]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 105:   7%|▏ | 105/1495 [00:40<09:56,  2.33it/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>What distortion occurs in this 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>What is the overall brightness of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall brightness of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall brightness of the image?\nA. Medium\nB. High\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], 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]: 0.8571,[Response]: C.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 105:   7%|▏ | 106/1495 [00:41<09:03,  2.56it/s]
[Running Accuracy]: 0.8585,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 106:   7%|▋         | 106/1495 [00:41<09:03,  2.56it/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>What is the overall 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>Does this image have motion-blur related issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have motion-blur related issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have motion-blur related issues?\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]: 0.8585,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 106:   7%|▋         | 107/1495 [00:42<12:23,  1.87it/s]
[Running Accuracy]: 0.8598,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 107:   7%|▊           | 107/1495 [00:42<12:23,  1.87it/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>Does this image have motion-blur related 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 severely blurred is the image?
A. Not blurred
B. Strongly blurred
C. Weakly blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severely blurred is the image?
A. Not blurred
B. Strongly blurred
C. Weakly blurred
Answer with the option's letter from the given choices directly.

prompts: [["How severely blurred is the image?\nA. Not blurred\nB. Strongly blurred\nC. Weakly blurred\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]: 0.8598,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 107:   7%|▊           | 108/1495 [00:42<12:36,  1.83it/s]
[Running Accuracy]: 0.8611,[Response]: C.<|endoftext|>, [Correct Ans]: Weakly blurred, , [Prog]: 108:   7%| | 108/1495 [00:42<12:36,  1.83it/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 severely blurred is the image?\nA. Not blurred\nB. Strongly blurred\nC. Weakly blurred\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Bad\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])
 A.

[Running Accuracy]: 0.8611,[Response]: C.<|endoftext|>, [Correct Ans]: Weakly blurred, , [Prog]: 108:   7%| | 109/1495 [00:43<12:51,  1.80it/s
[Running Accuracy]: 0.8624,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 109:   7%|▊          | 109/1495 [00:43<12:51,  1.80it/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 clarity of the image?\nA. Bad\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>What is the worst distortion in this picture?
A. Out of focus
B. Underexopsure
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. Underexopsure
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. Underexopsure\nC. Noise\nD. 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])
 A.

[Running Accuracy]: 0.8624,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 109:   7%|▊          | 110/1495 [00:43<11:15,  2.05it/s]
[Running Accuracy]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 110:   7%|▏ | 110/1495 [00:43<11:15,  2.05it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Underexopsure\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>Which is the worst distortion in this image?
A. Noise
B. Blur
C. Compression Artifact
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the worst distortion in this image?
A. Noise
B. Blur
C. Compression Artifact
Answer with the option's letter from the given choices directly.

prompts: [["Which is the worst distortion in this image?\nA. Noise\nB. Blur\nC. Compression Artifact\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]: 0.8636,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 110:   7%|▏ | 111/1495 [00:44<12:52,  1.79it/s]
[Running Accuracy]: 0.8649,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 111:   7%|▋         | 111/1495 [00:44<12:52,  1.79it/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>Which is the worst distortion in this image?\nA. Noise\nB. Blur\nC. Compression Artifact\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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([-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]: 0.8649,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 111:   7%|▋         | 112/1495 [00:44<11:16,  2.04it/s]
[Running Accuracy]: 0.8661,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 112:   7%|▋         | 112/1495 [00:44<11:16,  2.04it/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 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>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([-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]: 0.8661,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 112:   8%|▊         | 113/1495 [00:45<11:10,  2.06it/s]
[Running Accuracy]: 0.8673,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 113:   8%|▊          | 113/1495 [00:45<11:10,  2.06it/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>Does this picture 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>How saturated is the color of the image?
A. High
B. Moderate
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How saturated is the color of the image?
A. High
B. Moderate
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How saturated is the color of the image?\nA. High\nB. Moderate\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]: 0.8673,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 113:   8%|▊          | 114/1495 [00:45<10:04,  2.28it/s]
[Running Accuracy]: 0.8596,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 114:   8%|▍     | 114/1495 [00:45<10:04,  2.28it/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 saturated is the color of the image?\nA. High\nB. Moderate\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 are the buildings in this picture?
A. Severe
B. Mild
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry are the buildings in this picture?
A. Severe
B. Mild
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry are the buildings in this picture?\nA. Severe\nB. Mild\nC. Moderate\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]: 0.8596,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 114:   8%|▍     | 115/1495 [00:46<11:49,  1.95it/s]
[Running Accuracy]: 0.8609,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 115:   8%|▌       | 115/1495 [00:46<11:49,  1.95it/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 blurry are the buildings in this picture?\nA. Severe\nB. Mild\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 the lotus in this image?
A. Vivid
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the lotus in this image?
A. Vivid
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the lotus in this image?\nA. Vivid\nB. Monotonous\nC. Medium\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]: 0.8609,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 115:   8%|▌       | 116/1495 [00:46<10:30,  2.19it/s]
[Running Accuracy]: 0.8621,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 116:   8%|▌       | 116/1495 [00:46<10:30,  2.19it/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 color of the lotus in this image?\nA. Vivid\nB. Monotonous\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 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([-31.3750], 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]: 0.8621,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 116:   8%|▋       | 117/1495 [00:46<09:36,  2.39it/s]
[Running Accuracy]: 0.8547,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 117:   8%|▊         | 117/1495 [00:46<09:36,  2.39it/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 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>Which object is the focus in the image?
A. Signboard
B. Electric pole
C. Tree
D. Car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in the image?
A. Signboard
B. Electric pole
C. Tree
D. Car
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in the image?\nA. Signboard\nB. Electric pole\nC. Tree\nD. Car\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]: 0.8547,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 117:   8%|▊         | 118/1495 [00:47<08:55,  2.57it/s]
[Running Accuracy]: 0.8559,[Response]: D.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 118:   8%|▊          | 118/1495 [00:47<08:55,  2.57it/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>Which object is the focus in the image?\nA. Signboard\nB. Electric pole\nC. Tree\nD. Car\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 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([-31.2969], 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]: 0.8559,[Response]: D.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 118:   8%|▉          | 119/1495 [00:47<08:29,  2.70it/s]
[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 119:   8%|▋       | 119/1495 [00:47<08:29,  2.70it/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 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>Is the girl 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 girl in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the girl in focus 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])
 B.

[Running Accuracy]: 0.8571,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 119:   8%|▋       | 120/1495 [00:47<08:11,  2.80it/s]
[Running Accuracy]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 120:   8%|▉          | 120/1495 [00:47<08:11,  2.80it/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>Is the girl 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>Which object in this picture has motion blur?
A. Tree
B. People
C. Sky
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this picture has motion blur?
A. Tree
B. People
C. Sky
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this picture has motion blur?\nA. Tree\nB. People\nC. Sky\nD. Ground\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]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 120:   8%|▉          | 121/1495 [00:48<09:12,  2.49it/s]
[Running Accuracy]: 0.8512,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 121:   8%|▋       | 121/1495 [00:48<09:12,  2.49it/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>Which object in this picture has motion blur?\nA. Tree\nB. People\nC. Sky\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>How is the color saturation of the berries 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 berries 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 berries in the image?\nA. Low\nB. High\nC. Moderate\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]: 0.8512,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 121:   8%|▋       | 122/1495 [00:48<09:02,  2.53it/s]
[Running Accuracy]: 0.8525,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 122:   8%|▊         | 122/1495 [00:48<09:02,  2.53it/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 color saturation of the berries 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>Which of the following quality issues 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 of the following quality issues 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 of the following quality issues 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([-30.9844], 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]: 0.8525,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 122:   8%|▊         | 123/1495 [00:48<08:46,  2.61it/s]
[Running Accuracy]: 0.8537,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 123:   8%| | 123/1495 [00:48<08:46,  2.61it/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>Which of the following quality issues 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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of 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 of the image?\nA. High\nB. Medium\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])
 A.

[Running Accuracy]: 0.8537,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 123:   8%| | 124/1495 [00:49<08:21,  2.73it/s]
[Running Accuracy]: 0.8548,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 124:   8%|▊         | 124/1495 [00:49<08:21,  2.73it/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 color saturation 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>What is the focus of this image?
A. The plane
B. The sky
C. The street light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the focus of this image?
A. The plane
B. The sky
C. The street light
Answer with the option's letter from the given choices directly.

prompts: [["What is the focus of this image?\nA. The plane\nB. The sky\nC. The street light\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]: 0.8548,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 124:   8%|▊         | 125/1495 [00:49<08:01,  2.85it/s]
[Running Accuracy]: 0.8480,[Response]: C.<|endoftext|>, [Correct Ans]: The plane, , [Prog]: 125:   8%|▍    | 125/1495 [00:49<08:01,  2.85it/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>What is the focus of this image?\nA. The plane\nB. The sky\nC. The street light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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([-31.0625], 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]: 0.8480,[Response]: C.<|endoftext|>, [Correct Ans]: The plane, , [Prog]: 125:   8%|▍    | 126/1495 [00:49<07:55,  2.88it/s]
[Running Accuracy]: 0.8492,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 126:   8%|█           | 126/1495 [00:49<07:55,  2.88it/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>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>What problems exist in the image?
A. Backlight
B. Underexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Backlight
B. Underexposure
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Backlight\nB. Underexposure\nC. Out of focus\nD. Motion blur\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]: 0.8492,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 126:   8%|█           | 127/1495 [00:50<07:45,  2.94it/s]
[Running Accuracy]: 0.8504,[Response]: A.<|endoftext|>, [Correct Ans]: Backlight, , [Prog]: 127:   8%|▍    | 127/1495 [00:50<07:45,  2.94it/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>What problems exist in the image?\nA. Backlight\nB. Underexposure\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>How would you rate the clarity of the human in 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 clarity of the human in 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 clarity of the human in this image?\nA. Medium\nB. Low\nC. High\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]: 0.8504,[Response]: A.<|endoftext|>, [Correct Ans]: Backlight, , [Prog]: 127:   9%|▍    | 128/1495 [00:50<07:43,  2.95it/s]
[Running Accuracy]: 0.8516,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 128:   9%|▊         | 128/1495 [00:50<07:43,  2.95it/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 would you rate the clarity of the human in 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>What is the major distortion in this image?
A. Underexposure
B. Blur
C. Compression Artifacts
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. Underexposure
B. Blur
C. Compression Artifacts
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Underexposure\nB. Blur\nC. Compression Artifacts\nD. Noise\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]: 0.8516,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 128:   9%|▊         | 129/1495 [00:50<07:39,  2.97it/s]
[Running Accuracy]: 0.8527,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 129:   9%|▊         | 129/1495 [00:50<07:39,  2.97it/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>What is the major distortion in this image?\nA. Underexposure\nB. Blur\nC. Compression Artifacts\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 clarity of this image?
A. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. Clear\nB. Moderate\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]: 0.8527,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 129:   9%|▊         | 130/1495 [00:51<07:30,  3.03it/s]
[Running Accuracy]: 0.8538,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 130:   9%|▋       | 130/1495 [00:51<07:30,  3.03it/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 clarity of this image?\nA. Clear\nB. Moderate\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 brightness issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have brightness issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have brightness issues?\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]: 0.8538,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 130:   9%|▋       | 131/1495 [00:51<09:27,  2.40it/s]
[Running Accuracy]: 0.8473,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 131:   9%|█           | 131/1495 [00:51<09:27,  2.40it/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>Does this image have brightness 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. Computer mouse
B. Man wearing denim jacket
C. Bookshelf
D. Man with black collar
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. Computer mouse
B. Man wearing denim jacket
C. Bookshelf
D. Man with black collar
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. Computer mouse\nB. Man wearing denim jacket\nC. Bookshelf\nD. Man with black collar\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]: 0.8473,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 131:   9%|█           | 132/1495 [00:52<08:54,  2.55it/s]
[Running Accuracy]: 0.8409,[Response]: B.<|endoftext|>, [Correct Ans]: Man with black collar, , [Prog]: 132:   9%| | 132/1495 [00:52<08:54,  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 the focus in this image?\nA. Computer mouse\nB. Man wearing denim jacket\nC. Bookshelf\nD. Man with black collar\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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. Flowers
B. Grass
C. Rock
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Flowers
B. Grass
C. Rock
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Flowers\nB. Grass\nC. Rock\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]: 0.8409,[Response]: B.<|endoftext|>, [Correct Ans]: Man with black collar, , [Prog]: 132:   9%| | 133/1495 [00:52<08:23,  2
[Running Accuracy]: 0.8421,[Response]: A.<|endoftext|>, [Correct Ans]: Flowers, , [Prog]: 133:   9%|▌      | 133/1495 [00:52<08:23,  2.70it/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>Where is the focus of this picture?\nA. Flowers\nB. Grass\nC. Rock\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any motion blur in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any motion blur in the 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])
 A.

[Running Accuracy]: 0.8421,[Response]: A.<|endoftext|>, [Correct Ans]: Flowers, , [Prog]: 133:   9%|▋      | 134/1495 [00:52<08:00,  2.83it/s]
[Running Accuracy]: 0.8433,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 134:   9%|█           | 134/1495 [00:52<08:00,  2.83it/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>Is there any 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 the image is blurry?
A. The street
B. The women on street
C. The man on motorbike
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is blurry?
A. The street
B. The women on street
C. The man on motorbike
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is blurry?\nA. The street\nB. The women on street\nC. The man on motorbike\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]: 0.8433,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 134:   9%|█           | 135/1495 [00:53<09:27,  2.40it/s]
[Running Accuracy]: 0.8444,[Response]: C.<|endoftext|>, [Correct Ans]: The man on motorbike, , [Prog]: 135:   9%| | 135/1495 [00:53<09:27,  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 blurry?\nA. The street\nB. The women on street\nC. The man on motorbike\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["How is the ambient lighting condition of this image?\nA. Bright\nB. Dark\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]: 0.8444,[Response]: C.<|endoftext|>, [Correct Ans]: The man on motorbike, , [Prog]: 135:   9%| | 136/1495 [00:53<09:16,  2.
[Running Accuracy]: 0.8456,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 136:   9%|▋       | 136/1495 [00:53<09:16,  2.44it/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 ambient lighting condition of this image?\nA. Bright\nB. 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 clairy of the sign?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clairy of the sign?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clairy of the sign?\nA. Low\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])
 C.

[Running Accuracy]: 0.8456,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 136:   9%|▋       | 137/1495 [00:54<10:09,  2.23it/s]
[Running Accuracy]: 0.8467,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 137:   9%|▉         | 137/1495 [00:54<10:09,  2.23it/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 clairy of the sign?\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 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([-31.1562], 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]: 0.8467,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 137:   9%|▉         | 138/1495 [00:54<09:15,  2.44it/s]
[Running Accuracy]: 0.8478,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 138:   9%|█           | 138/1495 [00:54<09:15,  2.44it/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>Is this image well-composed?\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. Overexposure
B. Noise
C. Motion blur
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. Overexposure
B. Noise
C. Motion blur
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Overexposure\nB. Noise\nC. Motion blur\nD. Underexposure\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]: 0.8478,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 138:   9%|█           | 139/1495 [00:54<08:53,  2.54it/s]
[Running Accuracy]: 0.8489,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 139:   9%|▊        | 139/1495 [00:54<08:53,  2.54it/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>What is the worst distortion in this picture?\nA. Overexposure\nB. Noise\nC. Motion blur\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 occurs in this image?
A. Noise
B. Blurriness
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion occurs in this image?
A. Noise
B. Blurriness
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion occurs in this image?\nA. Noise\nB. Blurriness\nC. Underexposure\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]: 0.8489,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 139:   9%|▊        | 140/1495 [00:55<08:36,  2.62it/s]
[Running Accuracy]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 140:   9%|▎   | 140/1495 [00:55<08:36,  2.62it/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>What distortion occurs in this image?\nA. Noise\nB. Blurriness\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 arrangement of elements in this image?
A. Poor
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. Poor
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. Poor\nB. Medium\nC. Good\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]: 0.8500,[Response]: B.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 140:   9%|▍   | 141/1495 [00:55<08:12,  2.75it/s]
[Running Accuracy]: 0.8511,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 141:   9%|▉         | 141/1495 [00:55<08:12,  2.75it/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 arrangement of elements in this image?\nA. Poor\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>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([-31.2656], 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]: 0.8511,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 141:   9%|▉         | 142/1495 [00:55<07:57,  2.83it/s]
[Running Accuracy]: 0.8521,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 142:   9%|█▏          | 142/1495 [00:55<07:57,  2.83it/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>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>How is the clarity 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 clarity of the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], 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]: 0.8521,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 142:  10%|█▏          | 143/1495 [00:56<07:58,  2.82it/s]
[Running Accuracy]: 0.8531,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 143:  10%|█          | 143/1495 [00:56<07:58,  2.82it/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 clarity 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 clear is the bird in 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 bird in this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the bird in this picture?\nA. Clear\nB. Normal\nC. Blurry\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]: 0.8531,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 143:  10%|█          | 144/1495 [00:56<08:07,  2.77it/s]
[Running Accuracy]: 0.8542,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 144:  10%|▊       | 144/1495 [00:56<08:07,  2.77it/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 clear is the bird in 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>How is the composition in this image?
A. Poor
B. Good
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Poor
B. Good
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Poor\nB. Good\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])
 C.

[Running Accuracy]: 0.8542,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 144:  10%|▊       | 145/1495 [00:57<07:56,  2.84it/s]
[Running Accuracy]: 0.8483,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 145:  10%|▉         | 145/1495 [00:57<07:56,  2.84it/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 composition in this image?\nA. Poor\nB. Good\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 blurry is this image?
A. Very blurry
B. Moderately blurry
C. Not blurry
D. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is this image?
A. Very blurry
B. Moderately blurry
C. Not blurry
D. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is this image?\nA. Very blurry\nB. Moderately blurry\nC. Not blurry\nD. Slightly blurry\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]: 0.8483,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 145:  10%|▉         | 146/1495 [00:57<07:41,  2.92it/s]
[Running Accuracy]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 146:  10%|▎  | 146/1495 [00:57<07:41,  2.92it/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 blurry is this image?\nA. Very blurry\nB. Moderately blurry\nC. Not blurry\nD. Slightly 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. Dark
B. Good
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Dark
B. Good
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Dark\nB. Good\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]: 0.8493,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 146:  10%|▎  | 147/1495 [00:57<07:37,  2.94it/s]
[Running Accuracy]: 0.8503,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 147:  10%|▉         | 147/1495 [00:57<07:37,  2.94it/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 bright is this picture?\nA. Dark\nB. Good\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 clear is the building in this picture?
A. Blurry
B. Fair
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the building in this picture?
A. Blurry
B. Fair
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the building in this picture?\nA. Blurry\nB. Fair\nC. Clear\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]: 0.8503,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 147:  10%|▉         | 148/1495 [00:58<08:46,  2.56it/s]
[Running Accuracy]: 0.8514,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 148:  10%|▉        | 148/1495 [00:58<08:46,  2.56it/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 clear is the building in this picture?\nA. Blurry\nB. Fair\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 distortion doesn't exist in this picture?
A. Noise
B. Underexposure
C. Overexposure
D. Motion blur
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. Underexposure
C. Overexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion doesn't exist in this picture?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. Motion blur\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]: 0.8514,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 148:  10%|▉        | 149/1495 [00:58<08:21,  2.68it/s]
[Running Accuracy]: 0.8456,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 149:  10%|▉        | 149/1495 [00:58<08:21,  2.68it/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>What distortion doesn't exist in this picture?\nA. Noise\nB. Underexposure\nC. Overexposure\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 lighting in the image sufficient and bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting in the image sufficient and bright?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting in the image sufficient and bright?\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]: 0.8456,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 149:  10%|▉        | 150/1495 [00:58<08:01,  2.79it/s]
[Running Accuracy]: 0.8467,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 150:  10%|█          | 150/1495 [00:58<08:01,  2.79it/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>Is the lighting in the image sufficient and 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 is the most color-rich object in the image?
A. The girl's hair
B. The girl's clothes
C. The background
D. The girl's face
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most color-rich object in the image?
A. The girl's hair
B. The girl's clothes
C. The background
D. The girl's face
Answer with the option's letter from the given choices directly.

prompts: [["What is the most color-rich object in the image?\nA. The girl's hair\nB. The girl's clothes\nC. The background\nD. The girl's face\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]: 0.8467,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 150:  10%|█          | 151/1495 [00:59<07:49,  2.86it/s]
[Running Accuracy]: 0.8477,[Response]: A.<|endoftext|>, [Correct Ans]: The girl's hair, , [Prog]: 151:  10%| | 151/1495 [00:59<07:49,  2.86it/
 {'prompt': "A chat between a curious 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 color-rich object in the image?\nA. The girl's hair\nB. The girl's clothes\nC. The background\nD. The girl's face\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 elephant 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 elephant 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 elephant in the image?\nA. Clear\nB. Moderate\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]: 0.8477,[Response]: A.<|endoftext|>, [Correct Ans]: The girl's hair, , [Prog]: 151:  10%| | 152/1495 [00:59<07:30,  2.98it/
[Running Accuracy]: 0.8421,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 152:  10%|▌     | 152/1495 [00:59<07:30,  2.98it/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 clear is the elephant 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 about the shaprness of the image?
A. Very Good
B. Very bad
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How about the shaprness of the image?
A. Very Good
B. Very bad
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How about the shaprness of the image?\nA. Very Good\nB. Very 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]: 0.8421,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 152:  10%|▌     | 153/1495 [00:59<07:30,  2.98it/s]
[Running Accuracy]: 0.8431,[Response]: B.<|endoftext|>, [Correct Ans]: Very bad, , [Prog]: 153:  10%|▌     | 153/1495 [00:59<07:30,  2.98it/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 about the shaprness of the image?\nA. Very Good\nB. Very 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 problems exist in the image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems exist in the image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the image?\nA. Underexposure\nB. Overexposure\nC. Motion blur\nD. Out of focus\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])
 D.

[Running Accuracy]: 0.8431,[Response]: B.<|endoftext|>, [Correct Ans]: Very bad, , [Prog]: 153:  10%|▌     | 154/1495 [01:00<07:18,  3.06it/s]
[Running Accuracy]: 0.8377,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 154:  10%|▏ | 154/1495 [01:00<07:18,  3.06it/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>What problems exist in the image?\nA. Underexposure\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>What is the richness of the image color?
A. Monotonous
B. Moderate
C. Rich
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the richness of the image color?
A. Monotonous
B. Moderate
C. Rich
Answer with the option's letter from the given choices directly.

prompts: [["What is the richness of the image color?\nA. Monotonous\nB. Moderate\nC. Rich\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]: 0.8377,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 154:  10%|▏ | 155/1495 [01:00<08:21,  2.67it/s]
[Running Accuracy]: 0.8323,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 155:  10%|▍   | 155/1495 [01:00<08:21,  2.67it/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>What is the richness of the image color?\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>Which object in the composition of this image is emphasized in the center?
A. The sky
B. The store
C. The ground
D. The girl taking a photo with a camera
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 sky
B. The store
C. The ground
D. The girl taking a photo with a camera
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 sky\nB. The store\nC. The ground\nD. The girl taking a photo with a camera\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]: 0.8323,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 155:  10%|▍   | 156/1495 [01:00<08:11,  2.72it/s]
[Running Accuracy]: 0.8333,[Response]: D.<|endoftext|>, [Correct Ans]: The girl taking a photo with a camera, , [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 object in the composition of this image is emphasized in the center?\nA. The sky\nB. The store\nC. The ground\nD. The girl taking a photo with a camera\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 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([-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]: 0.8333,[Response]: D.<|endoftext|>, [Correct Ans]: The girl taking a photo with a camera, , [Prog]: 156:  11%| | 157/1495 
[Running Accuracy]: 0.8280,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 157:  11%|▊       | 157/1495 [01:01<07:59,  2.79it/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 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 part of the image is over-exposed?
A. The sky
B. The road
C. The trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is over-exposed?
A. The sky
B. The road
C. The trees
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is over-exposed?\nA. The sky\nB. The road\nC. The trees\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]: 0.8280,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 157:  11%|▊       | 158/1495 [01:01<09:30,  2.34it/s]
[Running Accuracy]: 0.8291,[Response]: A.<|endoftext|>, [Correct Ans]: The sky, , [Prog]: 158:  11%|▋      | 158/1495 [01:01<09:30,  2.34it/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>Which part of the image is over-exposed?\nA. The sky\nB. The road\nC. The 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>Is part of the image content twisted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is part of the image content twisted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is part of the image content twisted?\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]: 0.8291,[Response]: A.<|endoftext|>, [Correct Ans]: The sky, , [Prog]: 158:  11%|▋      | 159/1495 [01:02<11:21,  1.96it/s]
[Running Accuracy]: 0.8302,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 159:  11%|█▏         | 159/1495 [01:02<11:21,  1.96it/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>Is part of the image content twisted?\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 focus of the image?
A. The groud
B. The trees
C. The tall building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main focus of the image?
A. The groud
B. The trees
C. The tall building
Answer with the option's letter from the given choices directly.

prompts: [["What is the main focus of the image?\nA. The groud\nB. The trees\nC. The tall building\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]: 0.8302,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 159:  11%|█▏         | 160/1495 [01:03<12:11,  1.83it/s]
[Running Accuracy]: 0.8313,[Response]: A.<|endoftext|>, [Correct Ans]: The groud, , [Prog]: 160:  11%|▌    | 160/1495 [01:03<12:11,  1.83it/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>What is the main focus of the image?\nA. The groud\nB. The trees\nC. The tall building\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. woman
B. potted plant
C. coffee cup
D. bookshelf
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. woman
B. potted plant
C. coffee cup
D. bookshelf
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. woman\nB. potted plant\nC. coffee cup\nD. bookshelf\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]: 0.8313,[Response]: A.<|endoftext|>, [Correct Ans]: The groud, , [Prog]: 160:  11%|▌    | 161/1495 [01:03<10:38,  2.09it/s]
[Running Accuracy]: 0.8323,[Response]: A.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 161:  11%|▉        | 161/1495 [01:03<10:38,  2.09it/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>What is the clearest object in the image?\nA. woman\nB. potted plant\nC. coffee cup\nD. bookshelf\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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([-31.3906], 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]: 0.8323,[Response]: A.<|endoftext|>, [Correct Ans]: woman, , [Prog]: 161:  11%|▉        | 162/1495 [01:03<09:39,  2.30it/s]
[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 162:  11%|█▏         | 162/1495 [01:03<09:39,  2.30it/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>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>How bright are the planes in this picture?
A. Bright
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright are the planes in this picture?
A. Bright
B. Dark
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright are the planes in this picture?\nA. Bright\nB. Dark\nC. Normal\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]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 162:  11%|█▏         | 163/1495 [01:04<08:54,  2.49it/s]
[Running Accuracy]: 0.8344,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 163:  11%|█         | 163/1495 [01:04<08:54,  2.49it/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 bright are the planes in this picture?\nA. Bright\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>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([-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]: 0.8344,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 163:  11%|█         | 164/1495 [01:04<08:17,  2.68it/s]
[Running Accuracy]: 0.8354,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 164:  11%|█▏         | 164/1495 [01:04<08:17,  2.68it/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 quality 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>Which object is emphasized in the composition of the image?
A. Other characters
B. Landslide
C. Man on the skateboard
D. Platform
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. Other characters
B. Landslide
C. Man on the skateboard
D. Platform
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Other characters\nB. Landslide\nC. Man on the skateboard\nD. Platform\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]: 0.8354,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 164:  11%|█▏         | 165/1495 [01:04<07:57,  2.79it/s]
[Running Accuracy]: 0.8364,[Response]: C.<|endoftext|>, [Correct Ans]: Man on the skateboard, , [Prog]: 165:  11%| | 165/1495 [01:04<07:57,  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 composition of the image?\nA. Other characters\nB. Landslide\nC. Man on the skateboard\nD. Platform\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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 colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image colorful?\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]: 0.8364,[Response]: C.<|endoftext|>, [Correct Ans]: Man on the skateboard, , [Prog]: 165:  11%| | 166/1495 [01:05<07:53,  2
[Running Accuracy]: 0.8373,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 166:  11%|█▏         | 166/1495 [01:05<07:53,  2.81it/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>Is the image 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 lighting of the image?
A. Too bright
B. Too dark
C. Just fine
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Too bright
B. Too dark
C. Just fine
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Too bright\nB. Too dark\nC. Just fine\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]: 0.8373,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 166:  11%|█▏         | 167/1495 [01:05<07:39,  2.89it/s]
[Running Accuracy]: 0.8383,[Response]: C.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 167:  11%|▌    | 167/1495 [01:05<07:39,  2.89it/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 lighting of the image?\nA. Too bright\nB. Too dark\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>To what extent is the architecture in this image blurry?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the architecture in this image blurry?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the architecture in this image blurry?\nA. Severe\nB. Moderate\nC. Slight\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]: 0.8383,[Response]: C.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 167:  11%|▌    | 168/1495 [01:05<07:39,  2.89it/s]
[Running Accuracy]: 0.8393,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 168:  11%|▉       | 168/1495 [01:05<07:39,  2.89it/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>To what extent is the architecture in this image blurry?\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 kind of visual impression does the image give?
A. Dark
B. Vibrant
C. Fresh
D. Happy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual impression does the image give?
A. Dark
B. Vibrant
C. Fresh
D. Happy
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does the image give?\nA. Dark\nB. Vibrant\nC. Fresh\nD. Happy\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]: 0.8393,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 168:  11%|▉       | 169/1495 [01:06<07:30,  2.95it/s]
[Running Accuracy]: 0.8402,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 169:  11%|█▏        | 169/1495 [01:06<07:30,  2.95it/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>What kind of visual impression does the image give?\nA. Dark\nB. Vibrant\nC. Fresh\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>Is the subject clear and in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the subject clear and in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the subject clear and in focus?\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]: 0.8402,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 169:  11%|█▏        | 170/1495 [01:06<07:19,  3.02it/s]
[Running Accuracy]: 0.8412,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 170:  11%|█▎         | 170/1495 [01:06<07:19,  3.02it/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>Is the subject clear and 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 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([-30.7031], 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]: 0.8412,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 170:  11%|█▎         | 171/1495 [01:07<09:09,  2.41it/s]
[Running Accuracy]: 0.8421,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 171:  11%|█▎         | 171/1495 [01:07<09:09,  2.41it/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>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 this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image symmetrical?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image symmetrical?\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]: 0.8421,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 171:  12%|█▎         | 172/1495 [01:07<08:30,  2.59it/s]
[Running Accuracy]: 0.8430,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 172:  12%|█▎         | 172/1495 [01:07<08:30,  2.59it/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>Is 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 color saturation of the pizza 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 pizza 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 pizza in the image?\nA. Good\nB. Average\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])
 A.

[Running Accuracy]: 0.8430,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 172:  12%|█▎         | 173/1495 [01:07<08:07,  2.71it/s]
[Running Accuracy]: 0.8439,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 173:  12%|█▏        | 173/1495 [01:07<08:07,  2.71it/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 color saturation of the pizza 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>Which object in the image is not affected by motion blur?
A. Table lamp
B. Young girl
C. Tent
D. Adult
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. Table lamp
B. Young girl
C. Tent
D. Adult
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is not affected by motion blur?\nA. Table lamp\nB. Young girl\nC. Tent\nD. Adult\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]: 0.8439,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 173:  12%|█▏        | 174/1495 [01:08<07:43,  2.85it/s]
[Running Accuracy]: 0.8448,[Response]: B.<|endoftext|>, [Correct Ans]: Young girl, , [Prog]: 174:  12%|▍   | 174/1495 [01:08<07:43,  2.85it/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>Which object in the image is not affected by motion blur?\nA. Table lamp\nB. Young girl\nC. Tent\nD. Adult\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How saturated is the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How saturated is the image?\nA. Medium\nB. Low\nC. High\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]: 0.8448,[Response]: B.<|endoftext|>, [Correct Ans]: Young girl, , [Prog]: 174:  12%|▍   | 175/1495 [01:08<07:35,  2.90it/s]
[Running Accuracy]: 0.8457,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 175:  12%|█▏        | 175/1495 [01:08<07:35,  2.90it/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 saturated is 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 kind of visual feelings does the image evoke?
A. Joyful
B. Dark
C. Bright
D. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feelings does the image evoke?
A. Joyful
B. Dark
C. Bright
D. Clear
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feelings does the image evoke?\nA. Joyful\nB. Dark\nC. Bright\nD. 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])
 B.

[Running Accuracy]: 0.8457,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 175:  12%|█▏        | 176/1495 [01:08<07:19,  3.00it/s]
[Running Accuracy]: 0.8466,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 176:  12%|█▏        | 176/1495 [01:08<07:19,  3.00it/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>What kind of visual feelings does the image evoke?\nA. Joyful\nB. Dark\nC. Bright\nD. 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>Is the image color abundant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color abundant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color abundant?\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]: 0.8466,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 176:  12%|█▏        | 177/1495 [01:08<07:07,  3.08it/s]
[Running Accuracy]: 0.8475,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 177:  12%|█▎         | 177/1495 [01:08<07:07,  3.08it/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>Is the image color abundant?\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 focus of this image?
A. Floor
B. Wall
C. Table and chairs
D. Lamp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus of this image?
A. Floor
B. Wall
C. Table and chairs
D. Lamp
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus of this image?\nA. Floor\nB. Wall\nC. Table and chairs\nD. Lamp\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]: 0.8475,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 177:  12%|█▎         | 178/1495 [01:09<07:06,  3.09it/s]
[Running Accuracy]: 0.8483,[Response]: C.<|endoftext|>, [Correct Ans]: Table and chairs, , [Prog]: 178:  12%| | 178/1495 [01:09<07:06,  3.09it
 {'prompt': "A chat between 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 of this image?\nA. Floor\nB. Wall\nC. Table and chairs\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>Is the dog the focal point in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dog the focal point in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog the focal point in this image?\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]: 0.8483,[Response]: C.<|endoftext|>, [Correct Ans]: Table and chairs, , [Prog]: 178:  12%| | 179/1495 [01:09<07:07,  3.08it
[Running Accuracy]: 0.8492,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 179:  12%|█▎         | 179/1495 [01:09<07:07,  3.08it/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>Is the dog the focal point 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 clear is the ladybird 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 ladybird 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 ladybird in the image?\nA. Clear\nB. Blurry\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])
 A.

[Running Accuracy]: 0.8492,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 179:  12%|█▎         | 180/1495 [01:09<06:51,  3.20it/s]
[Running Accuracy]: 0.8444,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 180:  12%|▋     | 180/1495 [01:09<06:51,  3.20it/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 clear is the ladybird 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>Are the signs at the back 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 at the back clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the signs at the back clear in this picture?\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]: 0.8444,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 180:  12%|▋     | 181/1495 [01:10<06:51,  3.19it/s]
[Running Accuracy]: 0.8453,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 181:  12%|█▍          | 181/1495 [01:10<06:51,  3.19it/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>Are the signs at the back 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 kind of following distortion happen in this image?
A. Snow
B. Out-of-focus
C. Glare
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of following distortion happen in this image?
A. Snow
B. Out-of-focus
C. Glare
Answer with the option's letter from the given choices directly.

prompts: [["What kind of following distortion happen in this image?\nA. Snow\nB. Out-of-focus\nC. Glare\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]: 0.8453,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 181:  12%|█▍          | 182/1495 [01:10<08:36,  2.54it/s]
[Running Accuracy]: 0.8407,[Response]: B.<|endoftext|>, [Correct Ans]: Glare, , [Prog]: 182:  12%|█        | 182/1495 [01:10<08:36,  2.54it/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>What kind of following distortion happen in this image?\nA. Snow\nB. Out-of-focus\nC. Glare\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Poor
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition in this image?
A. Good
B. Poor
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition in this image?\nA. Good\nB. Poor\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])
 C.

[Running Accuracy]: 0.8407,[Response]: B.<|endoftext|>, [Correct Ans]: Glare, , [Prog]: 182:  12%|█        | 183/1495 [01:11<08:02,  2.72it/s]
[Running Accuracy]: 0.8415,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 183:  12%|▉       | 183/1495 [01:11<08:02,  2.72it/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 composition in this image?\nA. Good\nB. Poor\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 color does the in-focus part of the image have?
A. Green
B. Red
C. Black
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color does the in-focus part of the image have?
A. Green
B. Red
C. Black
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["Which color does the in-focus part of the image have?\nA. Green\nB. Red\nC. Black\nD. Blue\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]: 0.8415,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 183:  12%|▉       | 184/1495 [01:11<07:41,  2.84it/s]
[Running Accuracy]: 0.8424,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 184:  12%|█▎         | 184/1495 [01:11<07:41,  2.84it/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>Which color does the in-focus part of the image have?\nA. Green\nB. Red\nC. Black\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 the image include background bokeh?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image include background bokeh?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image include background bokeh?\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]: 0.8424,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 184:  12%|█▎         | 185/1495 [01:11<07:34,  2.88it/s]
[Running Accuracy]: 0.8378,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 185:  12%|█▎         | 185/1495 [01:11<07:34,  2.88it/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>Does the image include background bokeh?\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 lighting sufficient for the trees in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting sufficient for the trees in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting sufficient for the trees in the image?\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]: 0.8378,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 185:  12%|█▎         | 186/1495 [01:12<07:28,  2.92it/s]
[Running Accuracy]: 0.8387,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 186:  12%|█▍          | 186/1495 [01:12<07:28,  2.92it/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>Is the lighting sufficient for the trees 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>In the composition of the image, is the dog emphasized as 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 dog emphasized as 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 dog emphasized as the center?\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]: 0.8387,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 186:  13%|█▌          | 187/1495 [01:12<07:11,  3.03it/s]
[Running Accuracy]: 0.8396,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 187:  13%|█▍         | 187/1495 [01:12<07:11,  3.03it/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>In the composition of the image, is the dog emphasized as 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>How is the color saturation of the sky 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 sky 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 sky 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]: 0.8396,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 187:  13%|█▍         | 188/1495 [01:12<07:06,  3.06it/s]
[Running Accuracy]: 0.8404,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 188:  13%|█▎        | 188/1495 [01:12<07:06,  3.06it/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 color saturation of the sky 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 this dog real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this dog real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this dog real?\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]: 0.8404,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 188:  13%|█▎        | 189/1495 [01:13<07:03,  3.08it/s]
[Running Accuracy]: 0.8413,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 189:  13%|█▌          | 189/1495 [01:13<07:03,  3.08it/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>Is this dog real?\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 richness of the image?
A. Rich
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color richness of the image?
A. Rich
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color richness of the image?\nA. Rich\nB. Moderate\nC. Monotonous\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]: 0.8413,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 189:  13%|█▌          | 190/1495 [01:13<07:10,  3.03it/s]
[Running Accuracy]: 0.8421,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 190:  13%|▌   | 190/1495 [01:13<07:10,  3.03it/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 color richness of the image?\nA. Rich\nB. Moderate\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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 middle of 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 for the human in middle of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting well-balanced for the human in middle of 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])
 B.

[Running Accuracy]: 0.8421,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 190:  13%|▌   | 191/1495 [01:13<07:45,  2.80it/s]
[Running Accuracy]: 0.8429,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 191:  13%|█▍         | 191/1495 [01:13<07:45,  2.80it/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>Is the lighting well-balanced for the human in middle 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 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([-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]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 191:  13%|█▍         | 192/1495 [01:14<07:40,  2.83it/s]
[Running Accuracy]: 0.8438,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 192:  13%|█▌          | 192/1495 [01:14<07:40,  2.83it/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>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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. 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 in this image?
A. Low light
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion in this image?\nA. Low light\nB. Blur\nC. Noise\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]: 0.8438,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 192:  13%|█▌          | 193/1495 [01:14<09:15,  2.34it/s]
[Running Accuracy]: 0.8446,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 193:  13%|█▎        | 193/1495 [01:14<09:15,  2.34it/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>What is the main distortion in 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>Does the human in this image contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the human in this image contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the human in this image contain rich texture?\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]: 0.8446,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 193:  13%|█▎        | 194/1495 [01:15<09:07,  2.37it/s]
[Running Accuracy]: 0.8454,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 194:  13%|█▍         | 194/1495 [01:15<09:07,  2.37it/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>Does the human in this image 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>How is the overall 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 overall 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 overall sharpness of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], 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]: 0.8454,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 194:  13%|█▍         | 195/1495 [01:15<08:32,  2.54it/s]
[Running Accuracy]: 0.8462,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 195:  13%|█▎        | 195/1495 [01:15<08:32,  2.54it/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 overall 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>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([-30.8750], 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]: 0.8462,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 195:  13%|█▎        | 196/1495 [01:15<08:06,  2.67it/s]
[Running Accuracy]: 0.8469,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 196:  13%|█▌          | 196/1495 [01:15<08:06,  2.67it/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>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>How is the color saturation of the banana 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 banana 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 banana in the image?\nA. Good\nB. Fair\nC. Poor\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]: 0.8469,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 196:  13%|█▌          | 197/1495 [01:16<07:48,  2.77it/s]
[Running Accuracy]: 0.8426,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 197:  13%|█▎        | 197/1495 [01:16<07:48,  2.77it/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 color saturation of the banana in 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>How is the overall exposure of the shorter building?
A. Just fine
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall exposure of the shorter building?
A. Just fine
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall exposure of the shorter building?\nA. Just fine\nB. Overexposed\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])
 C.

[Running Accuracy]: 0.8426,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 197:  13%|█▎        | 198/1495 [01:16<09:47,  2.21it/s]
[Running Accuracy]: 0.8434,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 198:  13%|▎ | 198/1495 [01:16<09:47,  2.21it/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 overall exposure of the shorter building?\nA. Just fine\nB. Overexposed\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Bad
B. Acceptable
C. Very good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of this image?
A. Bad
B. Acceptable
C. Very good
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. Bad\nB. Acceptable\nC. Very good\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]: 0.8434,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 198:  13%|▎ | 199/1495 [01:17<10:56,  1.97it/s]
[Running Accuracy]: 0.8442,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 199:  13%|▌   | 199/1495 [01:17<10:56,  1.97it/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 would you rate the clarity of this image?\nA. Bad\nB. Acceptable\nC. Very 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 quality problems exist in the image?
A. Overexposure
B. Underexposure
C. Motion blur
D. Compression distortion
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality problems exist in the image?
A. Overexposure
B. Underexposure
C. Motion blur
D. Compression distortion
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality problems exist in the image?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Compression distortion\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]: 0.8442,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 199:  13%|▌   | 200/1495 [01:17<09:47,  2.20it/s]
[Running Accuracy]: 0.8400,[Response]: B.<|endoftext|>, [Correct Ans]: Compression distortion, , [Prog]: 200:  13%|▏| 200/1495 [01:17<09:47,  
 {'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 kind of quality problems exist in the image?\nA. Overexposure\nB. Underexposure\nC. Motion blur\nD. Compression distortion\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 are the noises in this image?
A. Very severe
B. Somewhat severe
C. Not severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe are the noises in this image?
A. Very severe
B. Somewhat severe
C. Not severe
Answer with the option's letter from the given choices directly.

prompts: [["How severe are the noises in this image?\nA. Very severe\nB. Somewhat severe\nC. Not severe\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]: 0.8400,[Response]: B.<|endoftext|>, [Correct Ans]: Compression distortion, , [Prog]: 200:  13%|▏| 201/1495 [01:18<08:52,  
[Running Accuracy]: 0.8408,[Response]: A.<|endoftext|>, [Correct Ans]: Very severe, , [Prog]: 201:  13%|▍  | 201/1495 [01:18<08:52,  2.43it/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 severe are the noises in this image?\nA. Very severe\nB. Somewhat severe\nC. Not 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>How severe is the noise in this picture?
A. Moderate
B. Mild
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the noise in this picture?
A. Moderate
B. Mild
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the noise in this picture?\nA. Moderate\nB. Mild\nC. Severe\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]: 0.8408,[Response]: A.<|endoftext|>, [Correct Ans]: Very severe, , [Prog]: 201:  14%|▍  | 202/1495 [01:18<08:21,  2.58it/s]
[Running Accuracy]: 0.8416,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 202:  14%|█       | 202/1495 [01:18<08:21,  2.58it/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 severe is the noise in 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>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([-31.0938], 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]: 0.8416,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 202:  14%|█       | 203/1495 [01:18<07:46,  2.77it/s]
[Running Accuracy]: 0.8424,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 203:  14%|█▋          | 203/1495 [01:18<07:46,  2.77it/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>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 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([-31.0156], 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]: 0.8424,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 203:  14%|█▋          | 204/1495 [01:19<07:28,  2.88it/s]
[Running Accuracy]: 0.8382,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 204:  14%|▎ | 204/1495 [01:19<07:28,  2.88it/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>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>What is the main color tone in the image?
A. Purple
B. Yellow
C. Red
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone in the image?
A. Purple
B. Yellow
C. Red
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone in the image?\nA. Purple\nB. Yellow\nC. Red\nD. Black\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])
 D.

[Running Accuracy]: 0.8382,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 204:  14%|▎ | 205/1495 [01:19<07:25,  2.90it/s]
[Running Accuracy]: 0.8341,[Response]: D.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 205:  14%|█       | 205/1495 [01:19<07:25,  2.90it/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>What is the main color tone in the image?\nA. Purple\nB. Yellow\nC. Red\nD. Black\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 fresh 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 fresh visual experience?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a fresh visual experience?\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]: 0.8341,[Response]: D.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 205:  14%|█       | 206/1495 [01:19<07:27,  2.88it/s]
[Running Accuracy]: 0.8301,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 206:  14%|█▋          | 206/1495 [01:19<07:27,  2.88it/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>Does this image give a fresh 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>How severe is the motion blur in this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the motion blur in this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the motion blur in this picture?\nA. Mild\nB. Severe\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]: 0.8301,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 206:  14%|█▋          | 207/1495 [01:20<09:01,  2.38it/s]
[Running Accuracy]: 0.8309,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 207:  14%|█       | 207/1495 [01:20<09:01,  2.38it/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 severe is the motion blur in this picture?\nA. Mild\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>How would you rate the lighting of the cars 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 cars 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 cars in this image?\nA. Medium\nB. Dark\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]: 0.8309,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 207:  14%|█       | 208/1495 [01:20<08:27,  2.54it/s]
[Running Accuracy]: 0.8317,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 208:  14%|█       | 208/1495 [01:20<08:27,  2.54it/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 would you rate the lighting of the cars in this image?\nA. Medium\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>How does the sky in the image looks?
A. Foggy
B. Sunny
C. Snowy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How does the sky in the image looks?
A. Foggy
B. Sunny
C. Snowy
Answer with the option's letter from the given choices directly.

prompts: [["How does the sky in the image looks?\nA. Foggy\nB. Sunny\nC. Snowy\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]: 0.8317,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 208:  14%|█       | 209/1495 [01:21<09:41,  2.21it/s]
[Running Accuracy]: 0.8325,[Response]: A.<|endoftext|>, [Correct Ans]: Foggy, , [Prog]: 209:  14%|█▎       | 209/1495 [01:21<09:41,  2.21it/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 does the sky in the image looks?\nA. Foggy\nB. Sunny\nC. Snowy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

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

prompts: [["Is underexposure a serious issue in the image?\nA. Slight\nB. Moderate\nC. Severe\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])
 C.

[Running Accuracy]: 0.8325,[Response]: A.<|endoftext|>, [Correct Ans]: Foggy, , [Prog]: 209:  14%|█▎       | 210/1495 [01:21<08:55,  2.40it/s]
[Running Accuracy]: 0.8286,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 210:  14%|▊     | 210/1495 [01:21<08:55,  2.40it/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>Is underexposure a serious issue in the image?\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>How clear is the focus on the characters 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 focus on the characters 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 focus on the characters in the image?\nA. Poor\nB. Good\nC. Average\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]: 0.8286,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 210:  14%|▊     | 211/1495 [01:21<08:22,  2.56it/s]
[Running Accuracy]: 0.8294,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 211:  14%|█▍        | 211/1495 [01:21<08:22,  2.56it/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 clear is the focus on the characters 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 advertisement in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the advertisement in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the advertisement in this picture clear?\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]: 0.8294,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 211:  14%|█▍        | 212/1495 [01:22<09:43,  2.20it/s]
[Running Accuracy]: 0.8302,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 212:  14%|█▋          | 212/1495 [01:22<09:43,  2.20it/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>Is the advertisement 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>Which part of the image is over-exposed?
A. All
B. The bottom part
C. None
D. The top part
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is over-exposed?
A. All
B. The bottom part
C. None
D. The top part
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is over-exposed?\nA. All\nB. The bottom part\nC. None\nD. The top part\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. The bottom part

[Running Accuracy]: 0.8302,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 212:  14%|█▋          | 213/1495 [01:23<11:17,  1.89it/s]
[Running Accuracy]: 0.8310,[Response]: B. The bottom part<|endoftext|>, [Correct Ans]: The bottom part, , [Prog]: 213:  14%|▏| 213/1495 [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>Which part of the image is over-exposed?\nA. All\nB. The bottom part\nC. None\nD. The top part\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B. The bottom part<|endoftext|>'} 

prompt A chat between 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. 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 not 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 not 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([-30.9219], 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]: 0.8310,[Response]: B. The bottom part<|endoftext|>, [Correct Ans]: The bottom part, , [Prog]: 213:  14%|▏| 214/1495 [01:23
[Running Accuracy]: 0.8271,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 214:  14%|▎ | 214/1495 [01:23<09:48,  2.18it/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>Which of the following quality issues does this image not 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': 'B.<|endoftext|>'} 

prompt A chat 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([-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]: 0.8271,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 214:  14%|▎ | 215/1495 [01:23<08:58,  2.38it/s]
[Running Accuracy]: 0.8233,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 215:  14%|█▋          | 215/1495 [01:23<08:58,  2.38it/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>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 blurry is the background of the image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background of the image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background of the image?\nA. Severe\nB. Moderate\nC. Slight\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]: 0.8233,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 215:  14%|█▋          | 216/1495 [01:24<08:15,  2.58it/s]
[Running Accuracy]: 0.8241,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 216:  14%|█▏      | 216/1495 [01:24<08:15,  2.58it/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 blurry is the background of the 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>Which object is emphasized in the center in terms of composition in this image?
A. Branch
B. Sky
C. Wood
D. Mouse
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center in terms of composition in this image?
A. Branch
B. Sky
C. Wood
D. Mouse
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center in terms of composition in this image?\nA. Branch\nB. Sky\nC. Wood\nD. Mouse\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]: 0.8241,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 216:  15%|█▏      | 217/1495 [01:24<08:01,  2.65it/s]
[Running Accuracy]: 0.8249,[Response]: D.<|endoftext|>, [Correct Ans]: Mouse, , [Prog]: 217:  15%|█▎       | 217/1495 [01:24<08:01,  2.65it/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>Which object is emphasized in the center in terms of composition in this image?\nA. Branch\nB. Sky\nC. Wood\nD. Mouse\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 refreshing visual sensation?
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 sensation?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing visual sensation?\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]: 0.8249,[Response]: D.<|endoftext|>, [Correct Ans]: Mouse, , [Prog]: 217:  15%|█▎       | 218/1495 [01:24<08:46,  2.42it/s]
[Running Accuracy]: 0.8257,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 218:  15%|█▌         | 218/1495 [01:24<08:46,  2.42it/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>Does this image give a refreshing visual sensation?\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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 B.

[Running Accuracy]: 0.8257,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 218:  15%|█▌         | 219/1495 [01:25<08:03,  2.64it/s]
[Running Accuracy]: 0.8219,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 219:  15%|█▌         | 219/1495 [01:25<08:03,  2.64it/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>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>Which part of this image is the brightest?
A. Ground
B. Pole
C. Net
D. Warning sign
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the brightest?
A. Ground
B. Pole
C. Net
D. Warning sign
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the brightest?\nA. Ground\nB. Pole\nC. Net\nD. Warning sign\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])
 D.

[Running Accuracy]: 0.8219,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 219:  15%|█▌         | 220/1495 [01:25<07:43,  2.75it/s]
[Running Accuracy]: 0.8227,[Response]: D.<|endoftext|>, [Correct Ans]: Warning sign, , [Prog]: 220:  15%|▎ | 220/1495 [01:25<07:43,  2.75it/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>Which part of this image is the brightest?\nA. Ground\nB. Pole\nC. Net\nD. Warning sign\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([-31.2812], 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]: 0.8227,[Response]: D.<|endoftext|>, [Correct Ans]: Warning sign, , [Prog]: 220:  15%|▎ | 221/1495 [01:25<07:24,  2.87it/s]
[Running Accuracy]: 0.8235,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 221:  15%|█▏      | 221/1495 [01:25<07:24,  2.87it/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 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>Is the fox emphasized as subject in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the fox emphasized as subject in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the fox emphasized as subject in the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.4531], 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]: 0.8235,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 221:  15%|█▏      | 222/1495 [01:26<07:19,  2.90it/s]
[Running Accuracy]: 0.8243,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 222:  15%|█▋         | 222/1495 [01:26<07:19,  2.90it/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>Is the fox emphasized as subject 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>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([-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]: 0.8243,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 222:  15%|█▋         | 223/1495 [01:26<07:08,  2.97it/s]
[Running Accuracy]: 0.8251,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 223:  15%|▏| 223/1495 [01:26<07:08,  2.97it/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>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': 'C.<|endoftext|>'} 

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

prompts: [["How sharp is the fur of the dog?\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])
 B.

[Running Accuracy]: 0.8251,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 223:  15%|▏| 224/1495 [01:26<06:56,  3.05it/s]
[Running Accuracy]: 0.8259,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 224:  15%|█▋         | 224/1495 [01:26<06:56,  3.05it/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 sharp is the fur of the dog?\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 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]: 0.8259,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 224:  15%|█▋         | 225/1495 [01:27<06:49,  3.10it/s]
[Running Accuracy]: 0.8267,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 225:  15%|█▊          | 225/1495 [01:27<06:49,  3.10it/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>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 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([-31.4375], 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]: 0.8267,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 225:  15%|█▊          | 226/1495 [01:27<06:52,  3.07it/s]
[Running Accuracy]: 0.8274,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 226:  15%|█▋         | 226/1495 [01:27<06:52,  3.07it/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>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 the man with a beard 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 man with a beard the main subject of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man with a beard the main subject of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.6250], 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]: 0.8274,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 226:  15%|█▋         | 227/1495 [01:27<06:49,  3.10it/s]
[Running Accuracy]: 0.8282,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 227:  15%|█▋         | 227/1495 [01:27<06:49,  3.10it/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>Is the man with a beard 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>What is the worst distortion in this picture?
A. Noise
B. Underexposure
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. Noise
B. Underexposure
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. Noise\nB. Underexposure\nC. Overexposure\nD. Motion blur\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])
 D.

[Running Accuracy]: 0.8282,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 227:  15%|█▋         | 228/1495 [01:28<06:44,  3.13it/s]
[Running Accuracy]: 0.8289,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 228:  15%|▍  | 228/1495 [01:28<06:44,  3.13it/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>What is the worst distortion in this picture?\nA. Noise\nB. Underexposure\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 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([-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]: 0.8289,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 228:  15%|▍  | 229/1495 [01:28<06:53,  3.06it/s]
[Running Accuracy]: 0.8297,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 229:  15%|█▊          | 229/1495 [01:28<06:53,  3.06it/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>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>How clear is the mane of the horse in the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the mane of the horse in the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the mane of the horse in the image?\nA. Good\nB. Moderate\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])
 B.

[Running Accuracy]: 0.8297,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 229:  15%|█▊          | 230/1495 [01:28<07:00,  3.01it/s]
[Running Accuracy]: 0.8304,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 230:  15%|▉     | 230/1495 [01:28<07:00,  3.01it/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 clear is the mane of the horse in the image?\nA. Good\nB. Moderate\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 people 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 people in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the people in focus in this picture?\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]: 0.8304,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 230:  15%|▉     | 231/1495 [01:29<06:57,  3.02it/s]
[Running Accuracy]: 0.8312,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 231:  15%|█▋         | 231/1495 [01:29<06:57,  3.02it/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>Is the people in focus 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>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([-30.8750], 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]: 0.8312,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 231:  16%|█▋         | 232/1495 [01:29<06:56,  3.03it/s]
[Running Accuracy]: 0.8319,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 232:  16%|█▋         | 232/1495 [01:29<06:56,  3.03it/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>Is the image color saturated?\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 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([-30.7969], 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]: 0.8319,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 232:  16%|█▋         | 233/1495 [01:29<07:07,  2.95it/s]
[Running Accuracy]: 0.8326,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 233:  16%|█▋         | 233/1495 [01:29<07:07,  2.95it/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>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>How is the color saturation of the cactus 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 cactus 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 cactus in the image?\nA. Poor\nB. Average\nC. Good\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]: 0.8326,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 233:  16%|█▋         | 234/1495 [01:30<06:58,  3.01it/s]
[Running Accuracy]: 0.8333,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 234:  16%|█▌        | 234/1495 [01:30<06:58,  3.01it/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 color saturation of the cactus 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 kind of weather-related distortion happens in the image?
A. Snow
B. Rain
C. Fog
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of weather-related distortion happens in the image?
A. Snow
B. Rain
C. Fog
Answer with the option's letter from the given choices directly.

prompts: [["What kind of weather-related distortion happens in the image?\nA. Snow\nB. Rain\nC. Fog\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]: 0.8333,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 234:  16%|█▌        | 235/1495 [01:30<09:11,  2.29it/s]
[Running Accuracy]: 0.8340,[Response]: C.<|endoftext|>, [Correct Ans]: Fog, , [Prog]: 235:  16%|█▋         | 235/1495 [01:30<09:11,  2.29it/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>What kind of weather-related distortion happens in the image?\nA. Snow\nB. Rain\nC. Fog\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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([-30.6406], 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])
 D.

[Running Accuracy]: 0.8340,[Response]: C.<|endoftext|>, [Correct Ans]: Fog, , [Prog]: 235:  16%|█▋         | 236/1495 [01:31<08:28,  2.47it/s]
[Running Accuracy]: 0.8347,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 236:  16%|▎ | 236/1495 [01:31<08:28,  2.47it/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>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': '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 emphasized in the center of this image composition?
A. Sky
B. Shop
C. Pedestrian
D. Hotel
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of this image composition?
A. Sky
B. Shop
C. Pedestrian
D. Hotel
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image composition?\nA. Sky\nB. Shop\nC. Pedestrian\nD. Hotel\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]: 0.8347,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 236:  16%|▎ | 237/1495 [01:31<07:57,  2.63it/s]
[Running Accuracy]: 0.8354,[Response]: D.<|endoftext|>, [Correct Ans]: Hotel, , [Prog]: 237:  16%|█▍       | 237/1495 [01:31<07:57,  2.63it/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>Which object is emphasized in the center of this image composition?\nA. Sky\nB. Shop\nC. Pedestrian\nD. Hotel\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 human in the middle very sharp?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the human in the middle very sharp?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the human in the middle very sharp?\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]: 0.8354,[Response]: D.<|endoftext|>, [Correct Ans]: Hotel, , [Prog]: 237:  16%|█▍       | 238/1495 [01:32<09:04,  2.31it/s]
[Running Accuracy]: 0.8361,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 238:  16%|█▉          | 238/1495 [01:32<09:04,  2.31it/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>Is the human in the middle very 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>Is the car in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the car in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the car in 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]: 0.8361,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 238:  16%|█▉          | 239/1495 [01:32<12:04,  1.73it/s]
[Running Accuracy]: 0.8368,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 239:  16%|█▊         | 239/1495 [01:32<12:04,  1.73it/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>Is the car 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>Is the composition of this image using the centered approach?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image using the centered approach?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image using the centered approach?\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]: 0.8368,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 239:  16%|█▊         | 240/1495 [01:33<10:21,  2.02it/s]
[Running Accuracy]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 240:  16%|█▉          | 240/1495 [01:33<10:21,  2.02it/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>Is the composition of this image using the centered approach?\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 quality level of this image?
A. Good
B. Medium
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the quality level of this image?
A. Good
B. Medium
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["What is the quality level of this image?\nA. Good\nB. Medium\nC. Poor\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]: 0.8333,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 240:  16%|█▉          | 241/1495 [01:33<09:17,  2.25it/s]
[Running Accuracy]: 0.8340,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 241:  16%|█▌        | 241/1495 [01:33<09:17,  2.25it/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>What is the quality level of this image?\nA. Good\nB. Medium\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 style is used in this image?
A. Rule of Thirds
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 style is used in this image?
A. Rule of Thirds
B. Shallow Depth-of-Field
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. Rule of Thirds\nB. Shallow Depth-of-Field\nC. Black and White\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]: 0.8340,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 241:  16%|█▌        | 242/1495 [01:33<08:45,  2.38it/s]
[Running Accuracy]: 0.8347,[Response]: C.<|endoftext|>, [Correct Ans]: Black and White, , [Prog]: 242:  16%|▏| 242/1495 [01:33<08:45,  2.38it/
 {'prompt': "A chat between 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. Rule of Thirds\nB. Shallow Depth-of-Field\nC. Black and White\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Person
B. Ground
C. Telephone booth
D. Building
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. Person
B. Ground
C. Telephone booth
D. Building
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is severely affected by motion blur?\nA. Person\nB. Ground\nC. Telephone booth\nD. Building\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]: 0.8347,[Response]: C.<|endoftext|>, [Correct Ans]: Black and White, , [Prog]: 242:  16%|▏| 243/1495 [01:34<08:01,  2.60it/
[Running Accuracy]: 0.8354,[Response]: A.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 243:  16%|█▎      | 243/1495 [01:34<08:01,  2.60it/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>Which object in the image is severely affected by motion blur?\nA. Person\nB. Ground\nC. Telephone booth\nD. Building\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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([-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]: 0.8354,[Response]: A.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 243:  16%|█▎      | 244/1495 [01:34<07:40,  2.72it/s]
[Running Accuracy]: 0.8361,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 244:  16%|█▋        | 244/1495 [01:34<07:40,  2.72it/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 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>How noisy is this image?
A. Not noisy
B. Slightly noisy
C. Very noisy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How noisy is this image?
A. Not noisy
B. Slightly noisy
C. Very noisy
Answer with the option's letter from the given choices directly.

prompts: [["How noisy is this image?\nA. Not noisy\nB. Slightly noisy\nC. Very noisy\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]: 0.8361,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 244:  16%|█▋        | 245/1495 [01:34<07:22,  2.83it/s]
[Running Accuracy]: 0.8367,[Response]: C.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 245:  16%|▋   | 245/1495 [01:34<07:22,  2.83it/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 noisy is this image?\nA. Not noisy\nB. Slightly noisy\nC. Very 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>Which man is more in focus?
A. The man in the left
B. The man in the right
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which man is more in focus?
A. The man in the left
B. The man in the right
Answer with the option's letter from the given choices directly.

prompts: [["Which man is more in focus?\nA. The man in the left\nB. The man in the right\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]: 0.8367,[Response]: C.<|endoftext|>, [Correct Ans]: Very noisy, , [Prog]: 245:  16%|▋   | 246/1495 [01:35<07:20,  2.83it/s]
[Running Accuracy]: 0.8374,[Response]: A.<|endoftext|>, [Correct Ans]: The man in the left, , [Prog]: 246:  16%|▏| 246/1495 [01:35<07:20,  2.8
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which man is more in focus?\nA. The man in the left\nB. The man in 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 lion statue totally in focus, partly in focus, or totally not in focus in this image?
A. Totally in focus
B. Partly in focus
C. Totally not in focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lion statue totally in focus, partly in focus, or totally not in focus in this image?
A. Totally in focus
B. Partly in focus
C. Totally not in focus
Answer with the option's letter from the given choices directly.

prompts: [["Is the lion statue totally in focus, partly in focus, or totally not in focus in this image?\nA. Totally in focus\nB. Partly in focus\nC. Totally not in focus\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]: 0.8374,[Response]: A.<|endoftext|>, [Correct Ans]: The man in the left, , [Prog]: 246:  17%|▏| 247/1495 [01:35<08:48,  2.3
[Running Accuracy]: 0.8381,[Response]: C.<|endoftext|>, [Correct Ans]: Totally not in focus, , [Prog]: 247:  17%|▏| 247/1495 [01:35<08:48,  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 lion statue totally in focus, partly in focus, or totally not in focus in this image?\nA. Totally in focus\nB. Partly in focus\nC. Totally not in 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 major distortion in this image?
A. Motion Blur
B. Noise
C. Compression Artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion in this image?
A. Motion Blur
B. Noise
C. Compression Artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Motion Blur\nB. Noise\nC. Compression Artifacts\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]: 0.8381,[Response]: C.<|endoftext|>, [Correct Ans]: Totally not in focus, , [Prog]: 247:  17%|▏| 248/1495 [01:36<10:38,  1.
[Running Accuracy]: 0.8387,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 248:  17%|▍  | 248/1495 [01:36<10:38,  1.95it/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>What is the major distortion in this image?\nA. Motion Blur\nB. Noise\nC. 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>Does this picture have noise issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise issues?\nA. Yes\nB. No\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]: 0.8387,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 248:  17%|▍  | 249/1495 [01:36<09:21,  2.22it/s]
[Running Accuracy]: 0.8394,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 249:  17%|█▊         | 249/1495 [01:36<09:21,  2.22it/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>Does this picture have noise 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>How is the overall clarity of this image?
A. Low
B. High
C. Acceptable
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. High
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Low\nB. High\nC. Acceptable\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]: 0.8394,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 249:  17%|█▊         | 250/1495 [01:37<08:36,  2.41it/s]
[Running Accuracy]: 0.8400,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 250:  17%|█▊         | 250/1495 [01:37<08:36,  2.41it/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 overall clarity of this image?\nA. Low\nB. High\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>How is the feeling on this image?
A. Cheerful
B. Adorable
C. Disgusting
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the feeling on this image?
A. Cheerful
B. Adorable
C. Disgusting
Answer with the option's letter from the given choices directly.

prompts: [["How is the feeling on this image?\nA. Cheerful\nB. Adorable\nC. Disgusting\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]: 0.8400,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 250:  17%|█▊         | 251/1495 [01:37<07:59,  2.59it/s]
[Running Accuracy]: 0.8406,[Response]: C.<|endoftext|>, [Correct Ans]: Disgusting, , [Prog]: 251:  17%|▋   | 251/1495 [01:37<07:59,  2.59it/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 feeling on this image?\nA. Cheerful\nB. Adorable\nC. Disgusting\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\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]: 0.8406,[Response]: C.<|endoftext|>, [Correct Ans]: Disgusting, , [Prog]: 251:  17%|▋   | 252/1495 [01:38<09:06,  2.28it/s]
[Running Accuracy]: 0.8373,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 252:  17%|█▋        | 252/1495 [01:38<09:06,  2.28it/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 clear is this picture?\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 severely affected by motion blur in the image?
A. Grass
B. Baseball bat
C. Ground
D. Baseball player
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is severely affected by motion blur in the image?
A. Grass
B. Baseball bat
C. Ground
D. Baseball player
Answer with the option's letter from the given choices directly.

prompts: [["Which object is severely affected by motion blur in the image?\nA. Grass\nB. Baseball bat\nC. Ground\nD. Baseball player\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]: 0.8373,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 252:  17%|█▋        | 253/1495 [01:38<08:18,  2.49it/s]
[Running Accuracy]: 0.8379,[Response]: B.<|endoftext|>, [Correct Ans]: Baseball bat, , [Prog]: 253:  17%|▎ | 253/1495 [01:38<08:18,  2.49it/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>Which object is severely affected by motion blur in the image?\nA. Grass\nB. Baseball bat\nC. Ground\nD. Baseball player\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 lighting artifacts in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any lighting artifacts in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there any lighting artifacts 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])
 A.

[Running Accuracy]: 0.8379,[Response]: B.<|endoftext|>, [Correct Ans]: Baseball bat, , [Prog]: 253:  17%|▎ | 254/1495 [01:38<08:45,  2.36it/s]
[Running Accuracy]: 0.8386,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 254:  17%|█▊         | 254/1495 [01:38<08:45,  2.36it/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>Are there any lighting artifacts 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>Where is the main focus of this picture?
A. People
B. Trees
C. Statue
D. Building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the main focus of this picture?
A. People
B. Trees
C. Statue
D. Building
Answer with the option's letter from the given choices directly.

prompts: [["Where is the main focus of this picture?\nA. People\nB. Trees\nC. Statue\nD. Building\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]: 0.8386,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 254:  17%|█▉         | 255/1495 [01:39<08:29,  2.43it/s]
[Running Accuracy]: 0.8392,[Response]: C.<|endoftext|>, [Correct Ans]: Statue, , [Prog]: 255:  17%|█▎      | 255/1495 [01:39<08:29,  2.43it/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>Where is the main focus of this picture?\nA. People\nB. Trees\nC. Statue\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 severe is the artifact in this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the artifact in this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the artifact in this picture?\nA. Mild\nB. Severe\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]: 0.8392,[Response]: C.<|endoftext|>, [Correct Ans]: Statue, , [Prog]: 255:  17%|█▎      | 256/1495 [01:39<07:53,  2.62it/s]
[Running Accuracy]: 0.8398,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 256:  17%|█▎      | 256/1495 [01:39<07:53,  2.62it/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 severe is the artifact in this picture?\nA. Mild\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>How is the lighting of people in the bottom of this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of people in the bottom of this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of people in the bottom of this image?\nA. Medium\nB. Dark\nC. Bright\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]: 0.8398,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 256:  17%|█▍      | 257/1495 [01:39<07:31,  2.74it/s]
[Running Accuracy]: 0.8405,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 257:  17%|█▋        | 257/1495 [01:39<07:31,  2.74it/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 lighting of people in the bottom of 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>How is the clarity of 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 clarity of the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Good\nB. Moderate\nC. Poor\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])
 A.

[Running Accuracy]: 0.8405,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 257:  17%|█▋        | 258/1495 [01:40<07:29,  2.75it/s]
[Running Accuracy]: 0.8411,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 258:  17%|█▋        | 258/1495 [01:40<07:29,  2.75it/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 clarity of 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>Does this image give people a feeling of cheerful visual enjoyment?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give people a feeling of cheerful visual enjoyment?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give people a feeling of cheerful visual enjoyment?\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]: 0.8411,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 258:  17%|█▋        | 259/1495 [01:40<07:22,  2.80it/s]
[Running Accuracy]: 0.8417,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 259:  17%|█▉         | 259/1495 [01:40<07:22,  2.80it/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>Does this image give people a feeling of cheerful 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>What's 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's 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's 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]: 0.8417,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 259:  17%|█▉         | 260/1495 [01:40<07:10,  2.87it/s]
[Running Accuracy]: 0.8423,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 260:  17%|█▌       | 260/1495 [01:40<07:10,  2.87it/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>What's 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>How is the image quality of this picture?
A. Very High
B. Very 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. Very High
B. Very Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the image quality of this picture?\nA. Very High\nB. Very Low\nC. Medium\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]: 0.8423,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 260:  17%|█▌       | 261/1495 [01:41<07:01,  2.93it/s]
[Running Accuracy]: 0.8429,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 261:  17%|█▍      | 261/1495 [01:41<07:01,  2.93it/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 quality of this picture?\nA. Very High\nB. Very Low\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>Does this image include motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image include motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image include motion 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]: 0.8429,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 261:  18%|█▍      | 262/1495 [01:41<06:51,  2.99it/s]
[Running Accuracy]: 0.8435,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 262:  18%|█▉         | 262/1495 [01:41<06:51,  2.99it/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>Does this image include 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>What is the main color tone of the image?
A. Black
B. Dark green
C. Yellow
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. Black
B. Dark green
C. Yellow
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the image?\nA. Black\nB. Dark green\nC. Yellow\nD. Red\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]: 0.8435,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 262:  18%|█▉         | 263/1495 [01:41<06:43,  3.05it/s]
[Running Accuracy]: 0.8441,[Response]: C.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 263:  18%|█▍      | 263/1495 [01:41<06:43,  3.05it/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>What is the main color tone of the image?\nA. Black\nB. Dark green\nC. Yellow\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. Building
B. Sky
C. Gate
D. Girl
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. Building
B. Sky
C. Gate
D. Girl
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. Building\nB. Sky\nC. Gate\nD. Girl\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])
 D.

[Running Accuracy]: 0.8441,[Response]: C.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 263:  18%|█▍      | 264/1495 [01:42<06:50,  3.00it/s]
[Running Accuracy]: 0.8447,[Response]: D.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 264:  18%|█▊        | 264/1495 [01:42<06:50,  3.00it/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>Which object in the composition of this image is emphasized in the center?\nA. Building\nB. Sky\nC. Gate\nD. Girl\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 in this picture?
A. Out of focus
B. Noise
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. Out of focus
B. Noise
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. Out of focus\nB. Noise\nC. Overexposure\nD. 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])
 A.

[Running Accuracy]: 0.8447,[Response]: D.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 264:  18%|█▊        | 265/1495 [01:42<06:49,  3.01it/s]
[Running Accuracy]: 0.8453,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 265:  18%|▎ | 265/1495 [01:42<06:49,  3.01it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Noise\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>Is the hair color of the girl in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the hair color of the girl in this image vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the hair color of the girl in this image vibrant?\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]: 0.8453,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 265:  18%|▎ | 266/1495 [01:42<06:56,  2.95it/s]
[Running Accuracy]: 0.8459,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 266:  18%|██▏         | 266/1495 [01:42<06:56,  2.95it/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>Is the hair color of the girl 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>What is the brightest part of the image?
A. Beam in the upper right corner
B. Metal staff
C. Satchel
D. Elderly person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part of the image?
A. Beam in the upper right corner
B. Metal staff
C. Satchel
D. Elderly person
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part of the image?\nA. Beam in the upper right corner\nB. Metal staff\nC. Satchel\nD. Elderly person\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]: 0.8459,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 266:  18%|██▏         | 267/1495 [01:43<07:01,  2.91it/s]
[Running Accuracy]: 0.8464,[Response]: A.<|endoftext|>, [Correct Ans]: Beam in the upper right corner, , [Prog]: 267:  18%|▏| 267/1495 [01:43<
 {'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 is the brightest part of the image?\nA. Beam in the upper right corner\nB. Metal staff\nC. Satchel\nD. Elderly person\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 frog in the image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the frog in the image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the frog in the image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6875], 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]: 0.8464,[Response]: A.<|endoftext|>, [Correct Ans]: Beam in the upper right corner, , [Prog]: 267:  18%|▏| 268/1495 [01:43<
[Running Accuracy]: 0.8470,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 268:  18%|█▊        | 268/1495 [01:43<06:57,  2.94it/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>What is the color saturation of the frog in the 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 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([-30.2812], 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]: 0.8470,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 268:  18%|█▊        | 269/1495 [01:43<06:51,  2.98it/s]
[Running Accuracy]: 0.8439,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 269:  18%|█▉         | 269/1495 [01:43<06:51,  2.98it/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>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>How blurry is 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 is 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 is 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([-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]: 0.8439,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 269:  18%|█▉         | 270/1495 [01:44<06:36,  3.09it/s]
[Running Accuracy]: 0.8444,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 270:  18%|▌  | 270/1495 [01:44<06:36,  3.09it/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 blurry is 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>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([-31.1094], 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]: 0.8444,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 270:  18%|▌  | 271/1495 [01:44<06:35,  3.10it/s]
[Running Accuracy]: 0.8450,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 271:  18%|██▏         | 271/1495 [01:44<06:35,  3.10it/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>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 is the sharpness of the image?
A. Fair
B. Bad
C. Poor
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. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Fair\nB. Bad\nC. Poor\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]: 0.8450,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 271:  18%|██▏         | 272/1495 [01:45<08:03,  2.53it/s]
[Running Accuracy]: 0.8419,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 272:  18%|█▊        | 272/1495 [01:45<08:03,  2.53it/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 sharpness of the image?\nA. Fair\nB. Bad\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 lighting of the builiding very good in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting of the builiding very good in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting of the builiding very good 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])
 A.

[Running Accuracy]: 0.8419,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 272:  18%|█▊        | 273/1495 [01:45<07:39,  2.66it/s]
[Running Accuracy]: 0.8388,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 273:  18%|██         | 273/1495 [01:45<07:39,  2.66it/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>Is the lighting of the builiding very good 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>What is the brightest color in this image?
A. Yellow
B. Purple
C. Gray
D. Green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. Yellow
B. Purple
C. Gray
D. Green
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. Yellow\nB. Purple\nC. Gray\nD. Green\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]: 0.8388,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 273:  18%|██         | 274/1495 [01:45<07:44,  2.63it/s]
[Running Accuracy]: 0.8358,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 274:  18%|█▋       | 274/1495 [01:45<07:44,  2.63it/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>What is the brightest color in this image?\nA. Yellow\nB. Purple\nC. Gray\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>What is feeling conveyed by this image?
A. Angry
B. Desolate
C. Pleasant
D. Cheerful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is feeling conveyed by this image?
A. Angry
B. Desolate
C. Pleasant
D. Cheerful
Answer with the option's letter from the given choices directly.

prompts: [["What is feeling conveyed by this image?\nA. Angry\nB. Desolate\nC. Pleasant\nD. Cheerful\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]: 0.8358,[Response]: A.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 274:  18%|█▋       | 275/1495 [01:46<07:27,  2.73it/s]
[Running Accuracy]: 0.8364,[Response]: B.<|endoftext|>, [Correct Ans]: Desolate, , [Prog]: 275:  18%|█     | 275/1495 [01:46<07:27,  2.73it/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>What is feeling conveyed by this image?\nA. Angry\nB. Desolate\nC. Pleasant\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's the focus of this image?
A. Poor
B. Good
C. Accptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus of this image?
A. Poor
B. Good
C. Accptable
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus of this image?\nA. Poor\nB. Good\nC. Accptable\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]: 0.8364,[Response]: B.<|endoftext|>, [Correct Ans]: Desolate, , [Prog]: 275:  18%|█     | 276/1495 [01:46<07:07,  2.85it/s]
[Running Accuracy]: 0.8370,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 276:  18%|█▊        | 276/1495 [01:46<07:07,  2.85it/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's the focus of this image?\nA. Poor\nB. Good\nC. Accptable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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([-30.9062], 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]: 0.8370,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 276:  19%|█▊        | 277/1495 [01:46<06:53,  2.94it/s]
[Running Accuracy]: 0.8339,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 277:  19%|██         | 277/1495 [01:46<06:53,  2.94it/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>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>Which quality issue exists 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
Which quality issue exists in the image?
A. Underexposure
B. Overexposure
C. Motion blur
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue exists 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([-30.9062], 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]: 0.8339,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 277:  19%|██         | 278/1495 [01:47<06:44,  3.01it/s]
[Running Accuracy]: 0.8309,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 278:  19%|█▋       | 278/1495 [01:47<06:44,  3.01it/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>Which quality issue exists 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': 'B.<|endoftext|>'} 

prompt A chat between 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 colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image colorful?\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]: 0.8309,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 278:  19%|█▋       | 279/1495 [01:47<06:39,  3.04it/s]
[Running Accuracy]: 0.8315,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 279:  19%|██         | 279/1495 [01:47<06:39,  3.04it/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>Is this image 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>Which color is the most eye-catching in the image?
A. Pink
B. Blue
C. Yellow
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. Pink
B. Blue
C. Yellow
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. Pink\nB. Blue\nC. Yellow\nD. Red\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]: 0.8315,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 279:  19%|██         | 280/1495 [01:47<06:36,  3.06it/s]
[Running Accuracy]: 0.8321,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 280:  19%|█▊        | 280/1495 [01:47<06:36,  3.06it/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>Which color is the most eye-catching in the image?\nA. Pink\nB. Blue\nC. Yellow\nD. 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>Where is the focus of this picture?
A. At the front
B. At the back
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. At the front
B. At the back
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. At the front\nB. At the back\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]: 0.8321,[Response]: B.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 280:  19%|█▉        | 281/1495 [01:48<06:30,  3.11it/s]
[Running Accuracy]: 0.8327,[Response]: A.<|endoftext|>, [Correct Ans]: At the front, , [Prog]: 281:  19%|▍ | 281/1495 [01:48<06:30,  3.11it/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>Where is the focus of this picture?\nA. At the front\nB. At the back\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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 this 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 this 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 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]: 0.8327,[Response]: A.<|endoftext|>, [Correct Ans]: At the front, , [Prog]: 281:  19%|▍ | 282/1495 [01:48<06:26,  3.13it/s]
[Running Accuracy]: 0.8333,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 282:  19%|██         | 282/1495 [01:48<06:26,  3.13it/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>Is the little boy 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>How clear is the focus on the subjects in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the focus on the subjects in the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the focus on the subjects in the image?\nA. Clear\nB. Medium\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])
 A.

[Running Accuracy]: 0.8333,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 282:  19%|██         | 283/1495 [01:48<06:28,  3.12it/s]
[Running Accuracy]: 0.8304,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 283:  19%|█▌      | 283/1495 [01:48<06:28,  3.12it/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 clear is the focus on the subjects 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>How is the sharpness of the man's face?
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 man's face?
A. Good
B. Fair
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the man's face?\nA. Good\nB. Fair\nC. Poor\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]: 0.8304,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 283:  19%|█▌      | 284/1495 [01:49<06:45,  2.98it/s]
[Running Accuracy]: 0.8310,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 284:  19%|█▉        | 284/1495 [01:49<06:45,  2.98it/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 sharpness of the man's face?\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>What is the color vividity of this image?
A. Faded, not yet black and white
B. Totally black and white
C. Vivid and saturated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color vividity of this image?
A. Faded, not yet black and white
B. Totally black and white
C. Vivid and saturated
Answer with the option's letter from the given choices directly.

prompts: [["What is the color vividity of this image?\nA. Faded, not yet black and white\nB. Totally black and white\nC. Vivid and saturated\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]: 0.8310,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 284:  19%|█▉        | 285/1495 [01:49<06:40,  3.02it/s]
[Running Accuracy]: 0.8316,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, not yet black and white, , [Prog]: 285:  19%|▏| 285/1495 [01:49<
 {'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 color vividity of this image?\nA. Faded, not yet black and white\nB. Totally black and white\nC. Vivid and 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>Is there any over-exposure on the wall?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any over-exposure on the wall?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any over-exposure on the wall?\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]: 0.8316,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, not yet black and white, , [Prog]: 285:  19%|▏| 286/1495 [01:50<
[Running Accuracy]: 0.8322,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 286:  19%|██         | 286/1495 [01:50<09:05,  2.22it/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>Is there any over-exposure on the wall?\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 focus of this image?
A. The blue flowers
B. The red flowers
C. The pink flowers
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the focus of this image?
A. The blue flowers
B. The red flowers
C. The pink flowers
Answer with the option's letter from the given choices directly.

prompts: [["What is the focus of this image?\nA. The blue flowers\nB. The red flowers\nC. The pink flowers\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])
 A.

[Running Accuracy]: 0.8322,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 286:  19%|██         | 287/1495 [01:50<08:23,  2.40it/s]
[Running Accuracy]: 0.8328,[Response]: A.<|endoftext|>, [Correct Ans]: The blue flowers, , [Prog]: 287:  19%|▏| 287/1495 [01:50<08:23,  2.40it
 {'prompt': "A chat between a curious 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 blue flowers\nB. The red flowers\nC. The pink flowers\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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([-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]: 0.8328,[Response]: A.<|endoftext|>, [Correct Ans]: The blue flowers, , [Prog]: 287:  19%|▏| 288/1495 [01:50<08:07,  2.48it
[Running Accuracy]: 0.8333,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 288:  19%|█▉        | 288/1495 [01:50<08:07,  2.48it/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 bright is this picture?\nA. Normal\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>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([-30.2344], 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]: 0.8333,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 288:  19%|█▉        | 289/1495 [01:51<07:40,  2.62it/s]
[Running Accuracy]: 0.8304,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 289:  19%|▍ | 289/1495 [01:51<07:40,  2.62it/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>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>What is the brightest part in this picture?
A. Ground
B. Building
C. Sky
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this picture?
A. Ground
B. Building
C. Sky
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this picture?\nA. Ground\nB. Building\nC. Sky\nD. Trees\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]: 0.8304,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 289:  19%|▍ | 290/1495 [01:51<09:16,  2.17it/s]
[Running Accuracy]: 0.8310,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 290:  19%|██▏        | 290/1495 [01:51<09:16,  2.17it/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>What is the brightest part in this picture?\nA. Ground\nB. Building\nC. Sky\nD. Trees\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. 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 the 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 the 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([-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]: 0.8310,[Response]: C.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 290:  19%|██▏        | 291/1495 [01:52<08:29,  2.36it/s]
[Running Accuracy]: 0.8316,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 291:  19%|▍ | 291/1495 [01:52<08:29,  2.36it/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>What problems exist in the 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': '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. Wood chips
B. Wild grass
C. Cat
D. Branch
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Wood chips
B. Wild grass
C. Cat
D. Branch
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Wood chips\nB. Wild grass\nC. Cat\nD. Branch\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]: 0.8316,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 291:  20%|▍ | 292/1495 [01:52<07:46,  2.58it/s]
[Running Accuracy]: 0.8322,[Response]: C.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 292:  20%|██▏        | 292/1495 [01:52<07:46,  2.58it/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>What is the clearest object in the image?\nA. Wood chips\nB. Wild grass\nC. Cat\nD. Branch\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. 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. Somewhat 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. Somewhat blurry\nB. Not blurry at all\nC. Very blurry\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]: 0.8322,[Response]: C.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 292:  20%|██▏        | 293/1495 [01:52<07:23,  2.71it/s]
[Running Accuracy]: 0.8328,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 293:  20%|▌  | 293/1495 [01:52<07:23,  2.71it/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 blurry is 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 of the following quality issues does not exist in this image?
A. Underexposure
B. Blur
C. Noise
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. Blur
C. Noise
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. Blur\nC. Noise\nD. Overexposure\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])
 A.

[Running Accuracy]: 0.8328,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 293:  20%|▌  | 294/1495 [01:53<07:04,  2.83it/s]
[Running Accuracy]: 0.8299,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 294:  20%|▍ | 294/1495 [01:53<07:04,  2.83it/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>Which of the following quality issues does not exist in this image?\nA. Underexposure\nB. Blur\nC. Noise\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 bright is the person in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is the person in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the person in this image?\nA. Medium\nB. Dark\nC. Bright\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]: 0.8299,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 294:  20%|▍ | 295/1495 [01:53<06:51,  2.92it/s]
[Running Accuracy]: 0.8271,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 295:  20%|█▌      | 295/1495 [01:53<06:51,  2.92it/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 bright is the person in this image?\nA. Medium\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>Which of the following quality issues does not exist in the image?
A. Underexposure
B. Overexposure
C. Noise
D. Motion Blur
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. Overexposure
C. Noise
D. Motion Blur
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. Overexposure\nC. Noise\nD. Motion 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]: 0.8271,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 295:  20%|█▌      | 296/1495 [01:53<06:51,  2.92it/s]
[Running Accuracy]: 0.8243,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 296:  20%|▌  | 296/1495 [01:53<06:51,  2.92it/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>Which of the following quality issues does not exist in the image?\nA. Underexposure\nB. Overexposure\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>How would you rate the clarity of the grass in 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 the grass in 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 the grass in this image?\nA. Medium\nB. High\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])
 C.

[Running Accuracy]: 0.8243,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 296:  20%|▌  | 297/1495 [01:54<06:36,  3.02it/s]
[Running Accuracy]: 0.8249,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 297:  20%|██▏        | 297/1495 [01:54<06:36,  3.02it/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 would you rate the clarity of the grass 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>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([-31.3438], 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]: 0.8249,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 297:  20%|██▏        | 298/1495 [01:54<07:01,  2.84it/s]
[Running Accuracy]: 0.8255,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 298:  20%|██▏        | 298/1495 [01:54<07:01,  2.84it/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>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 is the color 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 color 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 color saturation of the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3438], 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]: 0.8255,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 298:  20%|██▏        | 299/1495 [01:54<06:53,  2.89it/s]
[Running Accuracy]: 0.8261,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 299:  20%|██        | 299/1495 [01:54<06:53,  2.89it/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 color 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>How is the contrast level in this image?
A. Very High
B. Very Low
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast level in this image?
A. Very High
B. Very Low
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level in this image?\nA. Very High\nB. Very Low\nC. Average\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]: 0.8261,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 299:  20%|██        | 300/1495 [01:55<06:53,  2.89it/s]
[Running Accuracy]: 0.8267,[Response]: A.<|endoftext|>, [Correct Ans]: Very High, , [Prog]: 300:  20%|█    | 300/1495 [01:55<06:53,  2.89it/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 contrast level in this image?\nA. Very High\nB. Very Low\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 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([-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]: 0.8267,[Response]: A.<|endoftext|>, [Correct Ans]: Very High, , [Prog]: 300:  20%|█    | 301/1495 [01:55<06:45,  2.95it/s]
[Running Accuracy]: 0.8272,[Response]: B.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 301:  20%|█▊       | 301/1495 [01:55<06:45,  2.95it/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>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>Is there overexposure in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there overexposure in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there overexposure in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6562], 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]: 0.8272,[Response]: B.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 301:  20%|█▊       | 302/1495 [01:55<06:37,  3.00it/s]
[Running Accuracy]: 0.8278,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 302:  20%|██▏        | 302/1495 [01:55<06:37,  3.00it/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>Is there overexposure 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 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([-30.5781], 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]: 0.8278,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 302:  20%|██▏        | 303/1495 [01:56<06:30,  3.05it/s]
[Running Accuracy]: 0.8251,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 303:  20%|██        | 303/1495 [01:56<06:30,  3.05it/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 quality of this picture?\nA. Medium\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 focus at the back of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus at the back of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus at the back of this picture?\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]: 0.8251,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 303:  20%|██        | 304/1495 [01:56<06:36,  3.00it/s]
[Running Accuracy]: 0.8257,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 304:  20%|██▍         | 304/1495 [01:56<06:36,  3.00it/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>Is the focus at the back 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>What level of blurriness does this warning sign 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 this warning sign have?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness does this warning sign have?\nA. Severe\nB. Slight\nC. Moderate\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])
 A.

[Running Accuracy]: 0.8257,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 304:  20%|██▍         | 305/1495 [01:56<06:32,  3.03it/s]
[Running Accuracy]: 0.8230,[Response]: A.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 305:  20%|█▋      | 305/1495 [01:56<06:32,  3.03it/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>What level of blurriness does this warning sign 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 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([-31.1094], 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]: 0.8230,[Response]: A.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 305:  20%|█▋      | 306/1495 [01:57<06:34,  3.02it/s]
[Running Accuracy]: 0.8235,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 306:  20%|██        | 306/1495 [01:57<06:34,  3.02it/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 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>Does the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the ground contain rich texture?\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]: 0.8235,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 306:  21%|██        | 307/1495 [01:57<08:29,  2.33it/s]
[Running Accuracy]: 0.8241,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 307:  21%|██▎        | 307/1495 [01:57<08:29,  2.33it/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>Does 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>From which direction does the light source of the image come?
A. Side
B. Top and side
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light source of the image come?
A. Side
B. Top and side
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light source of the image come?\nA. Side\nB. Top and side\nC. Top\nD. Bottom\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]: 0.8241,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 307:  21%|██▎        | 308/1495 [01:58<07:50,  2.52it/s]
[Running Accuracy]: 0.8247,[Response]: B.<|endoftext|>, [Correct Ans]: Top and side, , [Prog]: 308:  21%|▍ | 308/1495 [01:58<07:50,  2.52it/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>From which direction does the light source of the image come?\nA. Side\nB. Top and side\nC. Top\nD. 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>What issues are there with this image?
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 issues are there with this image?
A. Overexposure
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What issues are there with this image?\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([-30.9844], 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]: 0.8247,[Response]: B.<|endoftext|>, [Correct Ans]: Top and side, , [Prog]: 308:  21%|▍ | 309/1495 [01:58<07:23,  2.68it/s]
[Running Accuracy]: 0.8252,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 309:  21%|▍ | 309/1495 [01:58<07:23,  2.68it/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>What issues are there with this image?\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': 'A.<|endoftext|>'} 

prompt A chat between a 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 higher on the left half of the image compared to the right half?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation higher on the left half of the image compared to the right half?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation higher on the left half of the image compared to the right half?\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]: 0.8252,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 309:  21%|▍ | 310/1495 [01:58<06:59,  2.82it/s]
[Running Accuracy]: 0.8226,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 310:  21%|██▍         | 310/1495 [01:58<06:59,  2.82it/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>Is the color saturation higher on the left half of the image compared to the right half?\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. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\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]: 0.8226,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 310:  21%|██▍         | 311/1495 [01:59<08:31,  2.31it/s]
[Running Accuracy]: 0.8199,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 311:  21%|██▍         | 311/1495 [01:59<08:31,  2.31it/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>Does this picture have underexposure 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 high contrast level?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have high contrast level?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have high contrast level?\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]: 0.8199,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 311:  21%|██▌         | 312/1495 [01:59<07:43,  2.55it/s]
[Running Accuracy]: 0.8205,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 312:  21%|██▌         | 312/1495 [01:59<07:43,  2.55it/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>Does this picture have high contrast level?\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. 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([-30.5469], 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]: 0.8205,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 312:  21%|██▌         | 313/1495 [01:59<07:12,  2.73it/s]
[Running Accuracy]: 0.8211,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 313:  21%|██▌         | 313/1495 [01:59<07:12,  2.73it/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>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>How would you rate the clarity 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 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 this image?\nA. Acceptable\nB. High\nC. Low\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]: 0.8211,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 313:  21%|██▌         | 314/1495 [02:00<06:54,  2.85it/s]
[Running Accuracy]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 314:  21%|██▎        | 314/1495 [02:00<06:54,  2.85it/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 would you rate the clarity 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>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([-31.0469], 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]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 314:  21%|██▎        | 315/1495 [02:00<06:45,  2.91it/s]
[Running Accuracy]: 0.8190,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 315:  21%|██        | 315/1495 [02:00<06:45,  2.91it/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 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>What is the color of the plastic tube in this image?
A. Moderate
B. Monotone
C. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color of the plastic tube in this image?
A. Moderate
B. Monotone
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["What is the color of the plastic tube in this image?\nA. Moderate\nB. Monotone\nC. Vibrant\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]: 0.8190,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 315:  21%|██        | 316/1495 [02:00<06:37,  2.96it/s]
[Running Accuracy]: 0.8196,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 316:  21%|█▍     | 316/1495 [02:00<06:37,  2.96it/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>What is the color of the plastic tube in this image?\nA. Moderate\nB. Monotone\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["Is any car in this image motion blurred?\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]: 0.8196,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 316:  21%|█▍     | 317/1495 [02:01<08:53,  2.21it/s]
[Running Accuracy]: 0.8202,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 317:  21%|██▎        | 317/1495 [02:01<08:53,  2.21it/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>Is any car in this image motion 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>How clear is the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image?
A. Clear
B. Medium
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Clear\nB. Medium\nC. Blurry\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]: 0.8202,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 317:  21%|██▎        | 318/1495 [02:01<08:13,  2.38it/s]
[Running Accuracy]: 0.8176,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 318:  21%|█▋      | 318/1495 [02:01<08:13,  2.38it/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 clear is 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>How bright is the sky in 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 the sky in this picture?
A. Normal
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the sky in this picture?\nA. Normal\nB. Bright\nC. Dark\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]: 0.8176,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 318:  21%|█▋      | 319/1495 [02:02<07:34,  2.59it/s]
[Running Accuracy]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 319:  21%|██▏       | 319/1495 [02:02<07:34,  2.59it/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 bright is the sky in this picture?\nA. Normal\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>What kind of distortion exists in this image?
A. Noise
B. Overexposure
C. Motion blur
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion exists in this image?
A. Noise
B. Overexposure
C. Motion blur
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion exists in this image?\nA. Noise\nB. Overexposure\nC. Motion 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])
 B.

[Running Accuracy]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 319:  21%|██▏       | 320/1495 [02:02<07:10,  2.73it/s]
[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 320:  21%|▍ | 320/1495 [02:02<07:10,  2.73it/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>What kind of distortion exists in this image?\nA. Noise\nB. Overexposure\nC. Motion blur\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 the human main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the human main subject highlighted?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the human main subject highlighted?\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]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 320:  21%|▍ | 321/1495 [02:02<07:06,  2.75it/s]
[Running Accuracy]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 321:  21%|██▎        | 321/1495 [02:02<07:06,  2.75it/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>Is the human 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 the color of 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 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 image rich?\nA. Monotonous\nB. Rich\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])
 B.

[Running Accuracy]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 321:  22%|██▎        | 322/1495 [02:03<06:51,  2.85it/s]
[Running Accuracy]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 322:  22%|▊   | 322/1495 [02:03<06:51,  2.85it/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>Is the color of 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>What is the most apparent distortion of the cars 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 most apparent distortion of the cars 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 most apparent distortion of the cars in this image?\nA. Noise\nB. Over-exposure\nC. Blur\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]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 322:  22%|▊   | 323/1495 [02:03<08:13,  2.38it/s]
[Running Accuracy]: 0.8173,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 323:  22%|██▏       | 323/1495 [02:03<08:13,  2.38it/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>What is the most apparent distortion of the cars 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>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([-31.2500], 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]: 0.8173,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 323:  22%|██▏       | 324/1495 [02:04<07:31,  2.59it/s]
[Running Accuracy]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 324:  22%|██▍        | 324/1495 [02:04<07:31,  2.59it/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>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 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([-31.1875], 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]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 324:  22%|██▍        | 325/1495 [02:04<07:06,  2.74it/s]
[Running Accuracy]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 325:  22%|██▌         | 325/1495 [02:04<07:06,  2.74it/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>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 of the woman sitting on the steps wearing a scarf clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image of the woman sitting on the steps wearing a scarf clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image of the woman sitting on the steps wearing a scarf 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]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 325:  22%|██▌         | 326/1495 [02:04<06:57,  2.80it/s]
[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 326:  22%|██▌         | 326/1495 [02:04<06:57,  2.80it/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>Is the image of the woman sitting on the steps wearing a scarf 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 object is the focus point in the image?
A. Beach
B. Person
C. Mountain
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus point in the image?
A. Beach
B. Person
C. Mountain
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus point in the image?\nA. Beach\nB. Person\nC. Mountain\nD. 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]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 326:  22%|██▌         | 327/1495 [02:05<06:40,  2.92it/s]
[Running Accuracy]: 0.8165,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 327:  22%|█▋      | 327/1495 [02:05<06:40,  2.92it/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>Which object is the focus point in the image?\nA. Beach\nB. Person\nC. Mountain\nD. 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>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([-30.2969], 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]: 0.8165,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 327:  22%|█▊      | 328/1495 [02:05<06:54,  2.81it/s]
[Running Accuracy]: 0.8171,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 328:  22%|██▋         | 328/1495 [02:05<06:54,  2.81it/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>Is this image out of 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>Which object is the brightest in the image?
A. Mudflat
B. Boat
C. Mountain
D. Sun
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the brightest in the image?
A. Mudflat
B. Boat
C. Mountain
D. Sun
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the brightest in the image?\nA. Mudflat\nB. Boat\nC. Mountain\nD. Sun\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. Sun

[Running Accuracy]: 0.8171,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 328:  22%|██▋         | 329/1495 [02:05<06:58,  2.79it/s]
[Running Accuracy]: 0.8176,[Response]: D. Sun<|endoftext|>, [Correct Ans]: Sun, , [Prog]: 329:  22%|█▌     | 329/1495 [02:05<06:58,  2.79it/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>Which object is the brightest in the image?\nA. Mudflat\nB. Boat\nC. Mountain\nD. Sun\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'D. Sun<|endoftext|>'} 

prompt A chat 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, which object is emphasized in the center?
A. Police
B. Ground
C. Vehicle
D. Pedestrian
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In this image, which object is emphasized in the center?
A. Police
B. Ground
C. Vehicle
D. Pedestrian
Answer with the option's letter from the given choices directly.

prompts: [["In this image, which object is emphasized in the center?\nA. Police\nB. Ground\nC. Vehicle\nD. Pedestrian\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]: 0.8176,[Response]: D. Sun<|endoftext|>, [Correct Ans]: Sun, , [Prog]: 329:  22%|█▌     | 330/1495 [02:06<06:49,  2.85it/s]
[Running Accuracy]: 0.8182,[Response]: A.<|endoftext|>, [Correct Ans]: Police, , [Prog]: 330:  22%|█▊      | 330/1495 [02:06<06:49,  2.85it/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>In this image, which object is emphasized in the center?\nA. Police\nB. Ground\nC. Vehicle\nD. Pedestrian\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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. Meidum
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. Meidum
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. Meidum\nB. Low\nC. High\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]: 0.8182,[Response]: A.<|endoftext|>, [Correct Ans]: Police, , [Prog]: 330:  22%|█▊      | 331/1495 [02:06<06:43,  2.89it/s]
[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 331:  22%|██▍        | 331/1495 [02:06<06:43,  2.89it/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 would you rate the clarity of this image?\nA. Meidum\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 color of the image rich?
A. Rich
B. Monotone
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the image rich?
A. Rich
B. Monotone
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image rich?\nA. Rich\nB. Monotone\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])
 B.

[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 331:  22%|██▍        | 332/1495 [02:06<06:44,  2.87it/s]
[Running Accuracy]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Monotone, , [Prog]: 332:  22%|█▎    | 332/1495 [02:06<06:44,  2.87it/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>Is the color of the image rich?\nA. Rich\nB. Monotone\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 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([-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]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Monotone, , [Prog]: 332:  22%|█▎    | 333/1495 [02:07<06:33,  2.95it/s]
[Running Accuracy]: 0.8198,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 333:  22%|█▎    | 333/1495 [02:07<06:33,  2.95it/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 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>How is the color saturation of the frog in 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 color saturation of the frog in the image?
A. Poor
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the frog in the image?\nA. Poor\nB. Good\nC. Fair\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]: 0.8198,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 333:  22%|█▎    | 334/1495 [02:07<06:29,  2.98it/s]
[Running Accuracy]: 0.8204,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 334:  22%|██▏       | 334/1495 [02:07<06:29,  2.98it/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 color saturation of the frog in the 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> How clear is the person on the right side of the image?
A. Moderate
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
 How clear is the person on the right side of the image?
A. Moderate
B. Clear
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [[" How clear is the person on the right side of the image?\nA. Moderate\nB. Clear\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])
 B.

[Running Accuracy]: 0.8204,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 334:  22%|██▏       | 335/1495 [02:07<06:13,  3.10it/s]
[Running Accuracy]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 335:  22%|█▎    | 335/1495 [02:07<06:13,  3.10it/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 clear is the person on the right side of the image?\nA. Moderate\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>Does this picture have compression issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have compression issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have compression issues?\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]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 335:  22%|█▎    | 336/1495 [02:08<06:15,  3.08it/s]
[Running Accuracy]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 336:  22%|██▍        | 336/1495 [02:08<06:15,  3.08it/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>Does this picture have compression 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>How 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
How 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: [["How 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([-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]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 336:  23%|██▍        | 337/1495 [02:08<06:29,  2.98it/s]
[Running Accuracy]: 0.8190,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 337:  23%|█▊      | 337/1495 [02:08<06:29,  2.98it/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 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': 'C.<|endoftext|>'} 

prompt A chat 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 shallow depth of field?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image include shallow depth of field?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image include shallow depth of field?\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]: 0.8190,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 337:  23%|█▊      | 338/1495 [02:08<06:33,  2.94it/s]
[Running Accuracy]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 338:  23%|██▍        | 338/1495 [02:08<06:33,  2.94it/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>Does this image include shallow depth of field?\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 good is the composition of this picture?
A. Fair
B. Poor
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. Poor
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. Poor\nC. Good\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]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 338:  23%|██▍        | 339/1495 [02:09<07:53,  2.44it/s]
[Running Accuracy]: 0.8201,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 339:  23%|██▎       | 339/1495 [02:09<07:53,  2.44it/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 good is the composition of this picture?\nA. Fair\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 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])
 A.

[Running Accuracy]: 0.8201,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 339:  23%|██▎       | 340/1495 [02:09<07:34,  2.54it/s]
[Running Accuracy]: 0.8206,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 340:  23%|██▋         | 340/1495 [02:09<07:34,  2.54it/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>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>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([-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]: 0.8206,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 340:  23%|██▋         | 341/1495 [02:10<08:34,  2.24it/s]
[Running Accuracy]: 0.8211,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 341:  23%|██▌        | 341/1495 [02:10<08:34,  2.24it/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>Does this picture 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>How blurry is the flower in 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 flower in 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 flower in 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([-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]: 0.8211,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 341:  23%|██▌        | 342/1495 [02:10<07:50,  2.45it/s]
[Running Accuracy]: 0.8216,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 342:  23%|▋  | 342/1495 [02:10<07:50,  2.45it/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 blurry is the flower in 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': 'B.<|endoftext|>'} 

prompt A chat between 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 effects are used in the image?
A. Bokeh
B. Black and white filter
C. Shallow depth of field
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of photography effects are used in the image?
A. Bokeh
B. Black and white filter
C. Shallow depth of field
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of photography effects are used in the image?\nA. Bokeh\nB. Black and white filter\nC. Shallow depth of field\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])
 A.

[Running Accuracy]: 0.8216,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 342:  23%|▋  | 343/1495 [02:11<07:21,  2.61it/s]
[Running Accuracy]: 0.8222,[Response]: A.<|endoftext|>, [Correct Ans]: Bokeh, , [Prog]: 343:  23%|██       | 343/1495 [02:11<07:21,  2.61it/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>What kind of photography effects are used in the image?\nA. Bokeh\nB. Black and white filter\nC. Shallow depth of field\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 the color saturation of the butterfly wings in the image high?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the butterfly wings in the image high?
A. Low
B. Moderate
C. High
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the butterfly wings in the image high?\nA. Low\nB. Moderate\nC. High\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]: 0.8222,[Response]: A.<|endoftext|>, [Correct Ans]: Bokeh, , [Prog]: 343:  23%|██       | 344/1495 [02:11<07:02,  2.72it/s]
[Running Accuracy]: 0.8198,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 344:  23%|█▍    | 344/1495 [02:11<07:02,  2.72it/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>Is the color saturation of the butterfly wings in the image high?\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>What issues are not present in the image?
A. Motion blur
B. Glare
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues are not present in the image?
A. Motion blur
B. Glare
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What issues are not present in the image?\nA. Motion blur\nB. Glare\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]: 0.8198,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 344:  23%|█▍    | 345/1495 [02:11<06:45,  2.84it/s]
[Running Accuracy]: 0.8203,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 345:  23%|▏| 345/1495 [02:11<06:45,  2.84it/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>What issues are not present in the image?\nA. Motion blur\nB. Glare\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 distortion most severely degrades the quality of this image?
A. Overexposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion most severely degrades the quality of this image?
A. Overexposure
B. Noise
C. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion most severely degrades the quality of this image?\nA. Overexposure\nB. Noise\nC. Motion 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]: 0.8203,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 345:  23%|▏| 346/1495 [02:12<08:16,  2.31it/s]
[Running Accuracy]: 0.8208,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 346:  23%|▋  | 346/1495 [02:12<08:16,  2.31it/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>What distortion most severely degrades the quality of this image?\nA. Overexposure\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>Which object in the image is emphasized in the center?
A. The little boy with the car
B. The big tree
C. The ground
D. The holly
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is emphasized in the center?
A. The little boy with the car
B. The big tree
C. The ground
D. The holly
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is emphasized in the center?\nA. The little boy with the car\nB. The big tree\nC. The ground\nD. The holly\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]: 0.8208,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 346:  23%|▋  | 347/1495 [02:12<07:37,  2.51it/s]
[Running Accuracy]: 0.8213,[Response]: A.<|endoftext|>, [Correct Ans]: The little boy with the car, , [Prog]: 347:  23%|▏| 347/1495 [02:12<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 object in the image is emphasized in the center?\nA. The little boy with the car\nB. The big tree\nC. The ground\nD. The holly\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 clearest?
A. The tree on the left side
B. The path
C. The castle on the left side
D. The castle on the right side
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the clearest?
A. The tree on the left side
B. The path
C. The castle on the left side
D. The castle on the right side
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the clearest?\nA. The tree on the left side\nB. The path\nC. The castle on the left side\nD. The castle on the right side\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])
 D.

[Running Accuracy]: 0.8213,[Response]: A.<|endoftext|>, [Correct Ans]: The little boy with the car, , [Prog]: 347:  23%|▏| 348/1495 [02:12<07:
[Running Accuracy]: 0.8190,[Response]: D.<|endoftext|>, [Correct Ans]: The tree on the left side, , [Prog]: 348:  23%|▏| 348/1495 [02:12<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>Which object in the image is the clearest?\nA. The tree on the left side\nB. The path\nC. The castle on the left side\nD. The castle on the right side\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 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 overall 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 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([-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]: 0.8190,[Response]: D.<|endoftext|>, [Correct Ans]: The tree on the left side, , [Prog]: 348:  23%|▏| 349/1495 [02:13<07:04
[Running Accuracy]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 349:  23%|█▊      | 349/1495 [02:13<07:04,  2.70it/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 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': 'A.<|endoftext|>'} 

prompt A chat between a 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([-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]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 349:  23%|█▊      | 350/1495 [02:13<06:59,  2.73it/s]
[Running Accuracy]: 0.8171,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 350:  23%|██▊         | 350/1495 [02:13<06:59,  2.73it/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>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': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.0938], 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]: 0.8171,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 350:  23%|██▊         | 351/1495 [02:13<06:44,  2.83it/s]
[Running Accuracy]: 0.8177,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 351:  23%|██▊         | 351/1495 [02:13<06:44,  2.83it/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>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>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([-30.7812], 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]: 0.8177,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 351:  24%|██▊         | 352/1495 [02:14<06:41,  2.84it/s]
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 352:  24%|██▌        | 352/1495 [02:14<06:41,  2.84it/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>Does this picture have overexposure 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>Are the children composed in the cnter of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the children composed in the cnter of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the children composed in the cnter 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]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 352:  24%|██▌        | 353/1495 [02:14<06:35,  2.89it/s]
[Running Accuracy]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 353:  24%|██▌        | 353/1495 [02:14<06:35,  2.89it/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>Are the children composed in the cnter 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 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([-31.3125], 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]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 353:  24%|██▌        | 354/1495 [02:15<06:41,  2.84it/s]
[Running Accuracy]: 0.8192,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 354:  24%|██▌        | 354/1495 [02:15<06:41,  2.84it/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>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>Are the people under the tent in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people under the tent in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the people under the tent in this picture clear?\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]: 0.8192,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 354:  24%|██▌        | 355/1495 [02:15<06:48,  2.79it/s]
[Running Accuracy]: 0.8169,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 355:  24%|██▊         | 355/1495 [02:15<06:48,  2.79it/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>Are the people under the tent 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>Is the lighting in the image bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting in the image bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting in the image bright?\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]: 0.8169,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 355:  24%|██▊         | 356/1495 [02:15<06:42,  2.83it/s]
[Running Accuracy]: 0.8174,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 356:  24%|██▌        | 356/1495 [02:15<06:42,  2.83it/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>Is the lighting in the image 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 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([-31.0156], 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]: 0.8174,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 356:  24%|██▋        | 357/1495 [02:16<06:31,  2.91it/s]
[Running Accuracy]: 0.8179,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 357:  24%|▏| 357/1495 [02:16<06:31,  2.91it/
 {'prompt': "A chat between 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>How is the brightness of the monitor in this image?
A. High
B. Low
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the monitor in this image?
A. High
B. Low
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the monitor in this image?\nA. High\nB. Low\nC. Average\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]: 0.8179,[Response]: C.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 357:  24%|▏| 358/1495 [02:16<07:15,  2.61it/
[Running Accuracy]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 358:  24%|██▋        | 358/1495 [02:16<07:15,  2.61it/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 brightness of the monitor in this image?\nA. High\nB. Low\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 overall clarity of this image?
A. Low
B. Very high
C. Acceptable
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. Very high
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Low\nB. Very high\nC. Acceptable\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]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 358:  24%|██▋        | 359/1495 [02:16<06:55,  2.73it/s]
[Running Accuracy]: 0.8162,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 359:  24%|▉   | 359/1495 [02:16<06:55,  2.73it/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 overall clarity of this image?\nA. Low\nB. Very high\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 image?
A. Window
B. Man in gray clothes
C. Ground
D. Man in white clothes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Window
B. Man in gray clothes
C. Ground
D. Man in white clothes
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Window\nB. Man in gray clothes\nC. Ground\nD. Man in white clothes\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])
 D.

[Running Accuracy]: 0.8162,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 359:  24%|▉   | 360/1495 [02:17<06:57,  2.72it/s]
[Running Accuracy]: 0.8167,[Response]: D.<|endoftext|>, [Correct Ans]: Man in white clothes, , [Prog]: 360:  24%|▏| 360/1495 [02:17<06:57,  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 brightest part in this image?\nA. Window\nB. Man in gray clothes\nC. Ground\nD. Man in white clothes\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 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([-31.0781], 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]: 0.8167,[Response]: D.<|endoftext|>, [Correct Ans]: Man in white clothes, , [Prog]: 360:  24%|▏| 361/1495 [02:17<06:41,  2.
[Running Accuracy]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 361:  24%|██▋        | 361/1495 [02:17<06:41,  2.83it/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>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>Does the human subject stand out in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the human subject stand out in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the human subject stand out 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]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 361:  24%|██▋        | 362/1495 [02:17<06:35,  2.86it/s]
[Running Accuracy]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 362:  24%|██▋        | 362/1495 [02:17<06:35,  2.86it/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>Does the human subject stand out 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 clear is the image of the wild geese?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image of the wild geese?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image of the wild geese?\nA. Clear\nB. Blurry\nC. Moderate\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]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 362:  24%|██▋        | 363/1495 [02:18<06:34,  2.87it/s]
[Running Accuracy]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 363:  24%|█▍    | 363/1495 [02:18<06:34,  2.87it/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 clear is the image of the wild geese?\nA. Clear\nB. Blurry\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>How is the clarity of the image?
A. Fair
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Fair
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Fair\nB. Poor\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])
 B.

[Running Accuracy]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 363:  24%|█▍    | 364/1495 [02:18<06:25,  2.93it/s]
[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 364:  24%|██▍       | 364/1495 [02:18<06:25,  2.93it/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 clarity of the image?\nA. Fair\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 color saturation of the bike in the image high?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the bike in the image high?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the bike in the image high?\nA. High\nB. Low\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])
 A. High

[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 364:  24%|██▍       | 365/1495 [02:18<06:30,  2.89it/s]
[Running Accuracy]: 0.8164,[Response]: A. High<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 365:  24%|▏| 365/1495 [02:18<06:30,  2.89it/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>Is the color saturation of the bike in the image high?\nA. High\nB. Low\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A. High<|endoftext|>'} 

prompt A chat between a 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. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image pyramid-shaped?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image pyramid-shaped?\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]: 0.8164,[Response]: A. High<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 365:  24%|▏| 366/1495 [02:19<06:28,  2.90it/s]
[Running Accuracy]: 0.8169,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 366:  24%|██▉         | 366/1495 [02:19<06:28,  2.90it/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>Is the composition of this image pyramid-shaped?\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 visual experience of the image?
A. Dull
B. Joyful
C. Fresh
D. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the visual experience of the image?
A. Dull
B. Joyful
C. Fresh
D. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["What is the visual experience of the image?\nA. Dull\nB. Joyful\nC. Fresh\nD. Vibrant\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]: 0.8169,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 366:  25%|██▉         | 367/1495 [02:19<06:18,  2.98it/s]
[Running Accuracy]: 0.8174,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 367:  25%|██▍       | 367/1495 [02:19<06:18,  2.98it/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>What is the visual experience of the image?\nA. Dull\nB. Joyful\nC. Fresh\nD. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the lighting like in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["What is the lighting like in this image?\nA. Medium\nB. Dark\nC. Bright\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]: 0.8174,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 367:  25%|██▍       | 368/1495 [02:20<07:27,  2.52it/s]
[Running Accuracy]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 368:  25%|██▍       | 368/1495 [02:20<07:27,  2.52it/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>What is the lighting like 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>Is this image aesthetically pleasing?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically pleasing?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically pleasing?\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]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 368:  25%|██▍       | 369/1495 [02:20<07:03,  2.66it/s]
[Running Accuracy]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 369:  25%|██▉         | 369/1495 [02:20<07:03,  2.66it/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>Is this image aesthetically pleasing?\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 wall painting contain rich textures?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the wall painting contain rich textures?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the wall painting contain rich textures?\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]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 369:  25%|██▉         | 370/1495 [02:21<08:15,  2.27it/s]
[Running Accuracy]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 370:  25%|██▋        | 370/1495 [02:21<08:15,  2.27it/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>Does the wall painting contain rich textures?\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 this image is the focus?
A. Pine tree
B. Bicycle
C. Plants in the red-gray flower pool
D. Street lamp
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the focus?
A. Pine tree
B. Bicycle
C. Plants in the red-gray flower pool
D. Street lamp
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the focus?\nA. Pine tree\nB. Bicycle\nC. Plants in the red-gray flower pool\nD. Street lamp\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]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 370:  25%|██▋        | 371/1495 [02:21<07:37,  2.45it/s]
[Running Accuracy]: 0.8194,[Response]: C.<|endoftext|>, [Correct Ans]: Plants in the red-gray flower pool, , [Prog]: 371:  25%|▏| 371/1495 [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 part of this image is the focus?\nA. Pine tree\nB. Bicycle\nC. Plants in the red-gray flower pool\nD. Street 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>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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.8194,[Response]: C.<|endoftext|>, [Correct Ans]: Plants in the red-gray flower pool, , [Prog]: 371:  25%|▏| 372/1495 [02
[Running Accuracy]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 372:  25%|█▉      | 372/1495 [02:21<07:07,  2.63it/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 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 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([-31.2656], 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]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 372:  25%|█▉      | 373/1495 [02:22<08:20,  2.24it/s]
[Running Accuracy]: 0.8177,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 373:  25%|██▏      | 373/1495 [02:22<08:20,  2.24it/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 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>How is the composition of the image?
A. Organized
B. Symmetrical
C. Chaotic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of the image?
A. Organized
B. Symmetrical
C. Chaotic
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of the image?\nA. Organized\nB. Symmetrical\nC. Chaotic\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]: 0.8177,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 373:  25%|██▎      | 374/1495 [02:22<09:00,  2.07it/s]
[Running Accuracy]: 0.8155,[Response]: A.<|endoftext|>, [Correct Ans]: Chaotic, , [Prog]: 374:  25%|█▊     | 374/1495 [02:22<09:00,  2.07it/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 composition of the image?\nA. Organized\nB. Symmetrical\nC. Chaotic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Ground
B. Big tree
C. Animal legs
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part of this image?
A. Ground
B. Big tree
C. Animal legs
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part of this image?\nA. Ground\nB. Big tree\nC. Animal legs\nD. Sky\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]: 0.8155,[Response]: A.<|endoftext|>, [Correct Ans]: Chaotic, , [Prog]: 374:  25%|█▊     | 375/1495 [02:23<08:23,  2.23it/s]
[Running Accuracy]: 0.8160,[Response]: C.<|endoftext|>, [Correct Ans]: Animal legs, , [Prog]: 375:  25%|▊  | 375/1495 [02:23<08:23,  2.23it/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>What is the clearest part of this image?\nA. Ground\nB. Big tree\nC. Animal legs\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>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([-31.4844], 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]: 0.8160,[Response]: C.<|endoftext|>, [Correct Ans]: Animal legs, , [Prog]: 375:  25%|▊  | 376/1495 [02:23<09:09,  2.04it/s]
[Running Accuracy]: 0.8165,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 376:  25%|█▌    | 376/1495 [02:23<09:09,  2.04it/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 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>Does this image come with correct color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image come with correct color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image come with correct color?\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]: 0.8165,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 376:  25%|█▌    | 377/1495 [02:24<08:20,  2.23it/s]
[Running Accuracy]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 377:  25%|███         | 377/1495 [02:24<08:20,  2.23it/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>Does this image come with correct 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>Does this picture have overexposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure?\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]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 377:  25%|███         | 378/1495 [02:24<07:54,  2.35it/s]
[Running Accuracy]: 0.8175,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 378:  25%|███         | 378/1495 [02:24<07:54,  2.35it/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>Does this picture have overexposure?\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 lighting of the image?
A. Dim
B. Bright
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Dim
B. Bright
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Dim\nB. Bright\nC. Average\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]: 0.8175,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 378:  25%|███         | 379/1495 [02:24<08:06,  2.29it/s]
[Running Accuracy]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 379:  25%|██▊        | 379/1495 [02:24<08:06,  2.29it/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 lighting of the image?\nA. Dim\nB. Bright\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 composition of this image centered?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image centered?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image centered?\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]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 379:  25%|██▊        | 380/1495 [02:25<07:32,  2.47it/s]
[Running Accuracy]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 380:  25%|██▊        | 380/1495 [02:25<07:32,  2.47it/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>Is the composition of this image centered?\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 stone 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 stone 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 stone 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([-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]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 380:  25%|██▊        | 381/1495 [02:25<07:00,  2.65it/s]
[Running Accuracy]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 381:  25%|██▊        | 381/1495 [02:25<07:00,  2.65it/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>Is the stone 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>Which object in the image has the highest sharpness?
A. Microphone
B. Clothing
C. Face
D. Hat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image has the highest sharpness?
A. Microphone
B. Clothing
C. Face
D. Hat
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image has the highest sharpness?\nA. Microphone\nB. Clothing\nC. Face\nD. Hat\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]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 381:  26%|██▊        | 382/1495 [02:25<06:34,  2.82it/s]
[Running Accuracy]: 0.8194,[Response]: A.<|endoftext|>, [Correct Ans]: Microphone, , [Prog]: 382:  26%|█   | 382/1495 [02:25<06:34,  2.82it/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>Which object in the image has the highest sharpness?\nA. Microphone\nB. Clothing\nC. Face\nD. Hat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 child's face?
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 child's face?
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 child's face?\nA. Overexposed\nB. Just fine\nC. Underexposed\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]: 0.8194,[Response]: A.<|endoftext|>, [Correct Ans]: Microphone, , [Prog]: 382:  26%|█   | 383/1495 [02:26<07:44,  2.39it/s]
[Running Accuracy]: 0.8198,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 383:  26%|█▎   | 383/1495 [02:26<07:44,  2.39it/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 exposure of the child's face?\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>How clear is this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this image?\nA. Acceptable\nB. Poor\nC. Good\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]: 0.8198,[Response]: B.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 383:  26%|█▎   | 384/1495 [02:26<07:18,  2.54it/s]
[Running Accuracy]: 0.8203,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 384:  26%|██▌       | 384/1495 [02:26<07:18,  2.54it/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 clear is this image?\nA. Acceptable\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>Is this image composed symmetrically?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image composed symmetrically?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image composed symmetrically?\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]: 0.8203,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 384:  26%|██▌       | 385/1495 [02:27<07:01,  2.63it/s]
[Running Accuracy]: 0.8208,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 385:  26%|██▊        | 385/1495 [02:27<07:01,  2.63it/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>Is this image composed symmetrically?\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 in focus in this picture?
A. Chair
B. Bottle
C. Painting
D. Cabinet
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is in focus in this picture?
A. Chair
B. Bottle
C. Painting
D. Cabinet
Answer with the option's letter from the given choices directly.

prompts: [["What is in focus in this picture?\nA. Chair\nB. Bottle\nC. Painting\nD. Cabinet\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]: 0.8208,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 385:  26%|██▊        | 386/1495 [02:27<06:50,  2.70it/s]
[Running Accuracy]: 0.8212,[Response]: B.<|endoftext|>, [Correct Ans]: Bottle, , [Prog]: 386:  26%|██      | 386/1495 [02:27<06:50,  2.70it/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>What is in focus in this picture?\nA. Chair\nB. Bottle\nC. Painting\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 composition of this image pyramid?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image pyramid?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image pyramid?\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]: 0.8212,[Response]: B.<|endoftext|>, [Correct Ans]: Bottle, , [Prog]: 386:  26%|██      | 387/1495 [02:27<06:37,  2.79it/s]
[Running Accuracy]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 387:  26%|███         | 387/1495 [02:27<06:37,  2.79it/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>Is the composition of this image pyramid?\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 in this image is the focus?
A. Plant
B. Street lamp
C. Sculpture
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. Plant
B. Street lamp
C. Sculpture
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. Plant\nB. Street lamp\nC. Sculpture\nD. Sky\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]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 387:  26%|███         | 388/1495 [02:28<06:26,  2.87it/s]
[Running Accuracy]: 0.8196,[Response]: C.<|endoftext|>, [Correct Ans]: Sculpture, , [Prog]: 388:  26%|█▎   | 388/1495 [02:28<06:26,  2.87it/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>Which object in this image is the focus?\nA. Plant\nB. Street lamp\nC. Sculpture\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's the worst distortion in this picture?
A. Overexposure
B. Out of focus
C. Noise
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. Noise
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. Noise\nD. Motion blur\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]: 0.8196,[Response]: C.<|endoftext|>, [Correct Ans]: Sculpture, , [Prog]: 388:  26%|█▎   | 389/1495 [02:28<07:09,  2.58it/s]
[Running Accuracy]: 0.8201,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 389:  26%|▌ | 389/1495 [02:28<07:09,  2.58it/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>What's the worst distortion in this picture?\nA. Overexposure\nB. Out of focus\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>Which of the following image quality problems does not exist in this picture?
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 image quality problems does not exist in this picture?
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 image quality problems does not exist in this picture?\nA. Underexposure\nB. Out of focus\nC. Overexposure\nD. Noise\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]: 0.8201,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 389:  26%|▌ | 390/1495 [02:28<06:54,  2.67it/s]
[Running Accuracy]: 0.8179,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 390:  26%|▎| 390/1495 [02:28<06:54,  2.67it/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>Which of the following image quality problems does not exist in this picture?\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>How is the color saturation of the sky in 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 color saturation of the sky in this image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the sky in this image?\nA. Medium\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])
 C.

[Running Accuracy]: 0.8179,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 390:  26%|▎| 391/1495 [02:29<06:30,  2.83it/s]
[Running Accuracy]: 0.8184,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 391:  26%|██▌       | 391/1495 [02:29<06:30,  2.83it/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 color saturation of the sky in 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 clarity of the background in the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the background in the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the background in the image?\nA. Moderate\nB. Blurry\nC. Clear\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]: 0.8184,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 391:  26%|██▌       | 392/1495 [02:29<06:24,  2.87it/s]
[Running Accuracy]: 0.8163,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 392:  26%|██      | 392/1495 [02:29<06:24,  2.87it/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 clarity of the background in the image?\nA. Moderate\nB. Blurry\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>What is the clearest object in the image?
A. Table
B. Chair
C. Billboard
D. Potted Plant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Table
B. Chair
C. Billboard
D. Potted Plant
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Table\nB. Chair\nC. Billboard\nD. Potted Plant\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]: 0.8163,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 392:  26%|██      | 393/1495 [02:29<06:11,  2.97it/s]
[Running Accuracy]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Table, , [Prog]: 393:  26%|██▎      | 393/1495 [02:29<06:11,  2.97it/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>What is the clearest object in the image?\nA. Table\nB. Chair\nC. Billboard\nD. Potted 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>Is the focus of this picture at the front 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 of this picture at the front or at the back?
A. Back
B. Front
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus of this picture at the front or at the back?\nA. Back\nB. Front\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]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Table, , [Prog]: 393:  26%|██▎      | 394/1495 [02:30<06:02,  3.04it/s]
[Running Accuracy]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: Back, , [Prog]: 394:  26%|██▋       | 394/1495 [02:30<06:02,  3.04it/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>Is the focus of this picture at the front or at the back?\nA. Back\nB. Front\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Motion blur
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. Over-exposure
B. Motion blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion of this image?\nA. Over-exposure\nB. Motion 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]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: Back, , [Prog]: 394:  26%|██▋       | 395/1495 [02:30<05:56,  3.08it/s]
[Running Accuracy]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 395:  26%|▊  | 395/1495 [02:30<05:56,  3.08it/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>What is the major distortion of this image?\nA. Over-exposure\nB. Motion 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 apparent distortion of the tent roof in 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 most apparent distortion of the tent roof in 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 most apparent distortion of the tent roof in this image?\nA. Low light\nB. Over-exposure\nC. Noise\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]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 395:  26%|▊  | 396/1495 [02:30<06:05,  3.00it/s]
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 396:  26%|▎| 396/1495 [02:30<06:05,  3.00it/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>What is the most apparent distortion of the tent roof in 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>Is the grass's texture 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 grass's texture very clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the grass's texture very clear in this image?\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]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 396:  27%|▎| 397/1495 [02:31<05:59,  3.05it/s]
[Running Accuracy]: 0.8186,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 397:  27%|██▉        | 397/1495 [02:31<05:59,  3.05it/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>Is the grass's texture 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>How does the color of the image look?
A. Faded
B. Saturated
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How does the color of the image look?
A. Faded
B. Saturated
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How does the color of the image look?\nA. Faded\nB. Saturated\nC. Average\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]: 0.8186,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 397:  27%|██▉        | 398/1495 [02:31<05:57,  3.07it/s]
[Running Accuracy]: 0.8191,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 398:  27%|██▍      | 398/1495 [02:31<05:57,  3.07it/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 does the color of the image look?\nA. Faded\nB. Saturated\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 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([-31.1406], 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]: 0.8191,[Response]: A.<|endoftext|>, [Correct Ans]: Faded, , [Prog]: 398:  27%|██▍      | 399/1495 [02:31<06:07,  2.98it/s]
[Running Accuracy]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 399:  27%|██▉        | 399/1495 [02:31<06:07,  2.98it/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>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>Which object is emphasized in the composition of the image?
A. Pink cyclist
B. Car
C. Pedestrian
D. Trees
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. Pink cyclist
B. Car
C. Pedestrian
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Pink cyclist\nB. Car\nC. Pedestrian\nD. Trees\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0938], 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]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 399:  27%|██▉        | 400/1495 [02:32<06:03,  3.02it/s]
[Running Accuracy]: 0.8200,[Response]: A.<|endoftext|>, [Correct Ans]: Pink cyclist, , [Prog]: 400:  27%|▌ | 400/1495 [02:32<06:03,  3.02it/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>Which object is emphasized in the composition of the image?\nA. Pink cyclist\nB. Car\nC. Pedestrian\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>Which object is emphasized in the composition of this image?
A. Sea water
B. Reef
C. Pilot
D. Plant
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. Sea water
B. Reef
C. Pilot
D. Plant
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. Sea water\nB. Reef\nC. Pilot\nD. Plant\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]: 0.8200,[Response]: A.<|endoftext|>, [Correct Ans]: Pink cyclist, , [Prog]: 400:  27%|▌ | 401/1495 [02:32<06:08,  2.97it/s]
[Running Accuracy]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Pilot, , [Prog]: 401:  27%|██▍      | 401/1495 [02:32<06:08,  2.97it/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>Which object is emphasized in the composition of this image?\nA. Sea water\nB. Reef\nC. Pilot\nD. Plant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman's head in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman's head in the image clear?\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]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Pilot, , [Prog]: 401:  27%|██▍      | 402/1495 [02:32<06:09,  2.96it/s]
[Running Accuracy]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 402:  27%|██▉        | 402/1495 [02:32<06:09,  2.96it/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>Is the woman's head 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 does the saturation of the raspberries look in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How does the saturation of the raspberries look in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How does the saturation of the raspberries look in the image?\nA. Medium\nB. Low\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.9375], 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]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 402:  27%|██▉        | 403/1495 [02:33<06:14,  2.92it/s]
[Running Accuracy]: 0.8189,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 403:  27%|██▋       | 403/1495 [02:33<06:14,  2.92it/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 does the saturation of the raspberries look 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 fox clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the fox clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the fox clear 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]: 0.8189,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 403:  27%|██▋       | 404/1495 [02:33<05:59,  3.04it/s]
[Running Accuracy]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 404:  27%|██▉        | 404/1495 [02:33<05:59,  3.04it/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>Is the fox 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 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([-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]: 0.8193,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 404:  27%|██▉        | 405/1495 [02:33<06:07,  2.97it/s]
[Running Accuracy]: 0.8198,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 405:  27%|██▉        | 405/1495 [02:33<06:07,  2.97it/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>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 is the clarity 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 clarity of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Poor\nB. Fair\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]: 0.8198,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 405:  27%|██▉        | 406/1495 [02:34<06:04,  2.99it/s]
[Running Accuracy]: 0.8202,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 406:  27%|██▋       | 406/1495 [02:34<06:04,  2.99it/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 clarity of the image?\nA. Poor\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>How is the color of this image as a wallpaper?
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 this image as a wallpaper?
A. Vibrant
B. Moderate
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of this image as a wallpaper?\nA. Vibrant\nB. Moderate\nC. Monotonous\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]: 0.8202,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 406:  27%|██▋       | 407/1495 [02:34<05:47,  3.13it/s]
[Running Accuracy]: 0.8206,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 407:  27%|█▉     | 407/1495 [02:34<05:47,  3.13it/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 color of this image as a wallpaper?\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 blurriness of 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 is the blurriness of 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 is the blurriness of 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([-31.2812], 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]: 0.8206,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 407:  27%|█▉     | 408/1495 [02:34<05:56,  3.05it/s]
[Running Accuracy]: 0.8186,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 408:  27%|▎| 408/1495 [02:34<05:56,  3.05i
 {'prompt': "A chat between a curious 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. Slightly 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>How bright is the buildings in 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 buildings in this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the buildings in this picture?\nA. Normal\nB. Dark\nC. Bright\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]: 0.8186,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 408:  27%|▎| 409/1495 [02:35<07:28,  2.42i
[Running Accuracy]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 409:  27%|██▋       | 409/1495 [02:35<07:28,  2.42it/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 bright is the buildings in 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>Are the details of the surfer clearly visible?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the details of the surfer clearly visible?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the details of the surfer clearly visible?\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]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 409:  27%|██▋       | 410/1495 [02:35<07:03,  2.56it/s]
[Running Accuracy]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 410:  27%|███▎        | 410/1495 [02:35<07:03,  2.56it/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>Are the details of the surfer clearly visible?\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 image has the brightest color?
A. Wood board
B. Flower
C. Weeds
D. Clover
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image has the brightest color?
A. Wood board
B. Flower
C. Weeds
D. Clover
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image has the brightest color?\nA. Wood board\nB. Flower\nC. Weeds\nD. Clover\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]: 0.8195,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 410:  27%|███▎        | 411/1495 [02:36<06:58,  2.59it/s]
[Running Accuracy]: 0.8175,[Response]: B.<|endoftext|>, [Correct Ans]: Clover, , [Prog]: 411:  27%|██▏     | 411/1495 [02:36<06:58,  2.59it/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>Which part of the image has the brightest color?\nA. Wood board\nB. Flower\nC. Weeds\nD. Clover\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.0625], 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]: 0.8175,[Response]: B.<|endoftext|>, [Correct Ans]: Clover, , [Prog]: 411:  28%|██▏     | 412/1495 [02:36<06:47,  2.66it/s]
[Running Accuracy]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 412:  28%|███▎        | 412/1495 [02:36<06:47,  2.66it/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>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>Where is the focus of this picture?
A. Center
B. Surrounding areas
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 areas
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Center\nB. Surrounding areas\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])
 A.

[Running Accuracy]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 412:  28%|███▎        | 413/1495 [02:36<06:28,  2.79it/s]
[Running Accuracy]: 0.8184,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 413:  28%|██▏     | 413/1495 [02:36<06:28,  2.79it/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>Where is the focus of this picture?\nA. Center\nB. 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 clarity of the faces 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 faces 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 faces in the image?\nA. Clear\nB. Medium\nC. Blurry\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]: 0.8184,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 413:  28%|██▏     | 414/1495 [02:37<06:14,  2.89it/s]
[Running Accuracy]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 414:  28%|██▏     | 414/1495 [02:37<06:14,  2.89it/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 clarity of the faces 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>What is the worst distortion in this image?
A. Noise
B. Underexposure
C. Overexposure
D. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the worst distortion in this image?
A. Noise
B. Underexposure
C. Overexposure
D. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this image?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. 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]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 414:  28%|██▏     | 415/1495 [02:37<07:27,  2.42it/s]
[Running Accuracy]: 0.8145,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 415:  28%|██▊       | 415/1495 [02:37<07:27,  2.42it/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>What is the worst distortion in this image?\nA. Noise\nB. Underexposure\nC. Overexposure\nD. 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 color saturation 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 color saturation of this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation 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]: 0.8145,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 415:  28%|██▊       | 416/1495 [02:38<06:55,  2.60it/s]
[Running Accuracy]: 0.8125,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 416:  28%|██▊       | 416/1495 [02:38<06:55,  2.60it/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 color saturation 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 emphasized in the center of this picture?
A. Mouse
B. Table
C. Hand
D. Laptop
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Mouse
B. Table
C. Hand
D. Laptop
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Mouse\nB. Table\nC. Hand\nD. Laptop\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]: 0.8125,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 416:  28%|██▊       | 417/1495 [02:38<06:35,  2.72it/s]
[Running Accuracy]: 0.8129,[Response]: A.<|endoftext|>, [Correct Ans]: Mouse, , [Prog]: 417:  28%|██▌      | 417/1495 [02:38<06:35,  2.72it/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>What is emphasized in the center of this picture?\nA. Mouse\nB. Table\nC. Hand\nD. Laptop\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 over-exposed parts on the background of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any over-exposed parts on the background of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any over-exposed parts on the background of the image?\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]: 0.8129,[Response]: A.<|endoftext|>, [Correct Ans]: Mouse, , [Prog]: 417:  28%|██▌      | 418/1495 [02:39<07:47,  2.30it/s]
[Running Accuracy]: 0.8134,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 418:  28%|███        | 418/1495 [02:39<07:47,  2.30it/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>Is there any over-exposed parts on the background 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>Which quality problem exists in the image?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality problem exists in the image?
A. Motion blur
B. Overexposure
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which quality problem exists in the image?\nA. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\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])
 A.

[Running Accuracy]: 0.8134,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 418:  28%|███        | 419/1495 [02:39<07:15,  2.47it/s]
[Running Accuracy]: 0.8138,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 419:  28%|▊  | 419/1495 [02:39<07:15,  2.47it/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>Which quality problem exists in the image?\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>Are the plants in focus in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the plants in focus in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the plants in focus in this photo?\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])
 A.

[Running Accuracy]: 0.8138,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 419:  28%|▊  | 420/1495 [02:39<07:15,  2.47it/s]
[Running Accuracy]: 0.8143,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 420:  28%|███▎        | 420/1495 [02:39<07:15,  2.47it/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>Are the plants in focus in this photo?\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 contents on the screen clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the contents on the screen clear in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the contents on the screen clear in this picture?\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])
 B.

[Running Accuracy]: 0.8143,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 420:  28%|███▍        | 421/1495 [02:40<08:09,  2.20it/s]
[Running Accuracy]: 0.8147,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 421:  28%|███▍        | 421/1495 [02:40<08:09,  2.20it/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>Are the contents on the screen 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>Does this image have a symmetrical composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have a symmetrical composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have a symmetrical composition?\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])
 B.

[Running Accuracy]: 0.8147,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 421:  28%|███▍        | 422/1495 [02:40<08:46,  2.04it/s]
[Running Accuracy]: 0.8152,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 422:  28%|███▍        | 422/1495 [02:40<08:46,  2.04it/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>Does this image have a symmetrical 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 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([-30.3438], 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]: 0.8152,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 422:  28%|███▍        | 423/1495 [02:41<07:54,  2.26it/s]
[Running Accuracy]: 0.8156,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 423:  28%|██▎     | 423/1495 [02:41<07:54,  2.26it/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 bright is this picture?\nA. Normal\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>Is there motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there motion blur in the image?\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])
 B.

[Running Accuracy]: 0.8156,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 423:  28%|██▎     | 424/1495 [02:41<07:12,  2.48it/s]
[Running Accuracy]: 0.8160,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 424:  28%|███▍        | 424/1495 [02:41<07:12,  2.48it/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>Is there motion blur 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 grey car 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
Is the grey car emphasized in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the grey car 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([-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]: 0.8160,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 424:  28%|███▍        | 425/1495 [02:41<06:51,  2.60it/s]
[Running Accuracy]: 0.8141,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 425:  28%|███▍        | 425/1495 [02:41<06:51,  2.60it/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>Is the grey car 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': 'B.<|endoftext|>'} 

prompt A chat between 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([-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]: 0.8141,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 425:  28%|███▍        | 426/1495 [02:42<06:24,  2.78it/s]
[Running Accuracy]: 0.8146,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 426:  28%|█▋    | 426/1495 [02:42<06:24,  2.78it/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 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>How is the lighting of this bike?
A. High
B. Low
C. Accepatable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this bike?
A. High
B. Low
C. Accepatable
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this bike?\nA. High\nB. Low\nC. Accepatable\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]: 0.8146,[Response]: B.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 426:  29%|█▋    | 427/1495 [02:42<07:43,  2.31it/s]
[Running Accuracy]: 0.8126,[Response]: B.<|endoftext|>, [Correct Ans]: Accepatable, , [Prog]: 427:  29%|▊  | 427/1495 [02:42<07:43,  2.31it/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 lighting of this bike?\nA. High\nB. Low\nC. Accepatable\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 appropriate in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus appropriate in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus appropriate 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]: 0.8126,[Response]: B.<|endoftext|>, [Correct Ans]: Accepatable, , [Prog]: 427:  29%|▊  | 428/1495 [02:43<06:57,  2.55it/s]
[Running Accuracy]: 0.8131,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 428:  29%|███▍        | 428/1495 [02:43<06:57,  2.55it/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>Is the focus appropriate 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 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([-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]: 0.8131,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 428:  29%|███▍        | 429/1495 [02:43<06:39,  2.67it/s]
[Running Accuracy]: 0.8135,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 429:  29%|██▎     | 429/1495 [02:43<06:39,  2.67it/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 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>Do the ground and trees contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the ground and trees contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the ground and trees contain rich texture?\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]: 0.8135,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 429:  29%|██▎     | 430/1495 [02:44<07:47,  2.28it/s]
[Running Accuracy]: 0.8140,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 430:  29%|███▍        | 430/1495 [02:44<07:47,  2.28it/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>Do the ground and trees contain rich 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>Which one of the following image quality issues does not 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
Which one of the following image quality issues does not 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: [["Which one of the following image quality issues does not 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([-31.4375], 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]: 0.8140,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 430:  29%|███▍        | 431/1495 [02:44<07:08,  2.48it/s]
[Running Accuracy]: 0.8144,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 431:  29%|▎| 431/1495 [02:44<07:08,  2.48it/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>Which one of the following image quality issues does not 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': 'C.<|endoftext|>'} 

prompt A chat between a 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 of the 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 of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bird emphasized in the center of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0781], 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]: 0.8144,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 431:  29%|▎| 432/1495 [02:44<06:48,  2.60it/s]
[Running Accuracy]: 0.8148,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 432:  29%|███▏       | 432/1495 [02:44<06:48,  2.60it/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>Is the bird emphasized 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>Are there any color aberrations 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 aberrations in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there any color aberrations 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]: 0.8148,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 432:  29%|███▏       | 433/1495 [02:44<06:26,  2.75it/s]
[Running Accuracy]: 0.8129,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 433:  29%|███▏       | 433/1495 [02:44<06:26,  2.75it/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>Are there any color aberrations 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 sky in this image noisy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky in this image noisy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky in this image noisy?\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]: 0.8129,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 433:  29%|███▏       | 434/1495 [02:45<07:34,  2.33it/s]
[Running Accuracy]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 434:  29%|███▍        | 434/1495 [02:45<07:34,  2.33it/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>Is the sky in this image noisy?\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. 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([-30.9375], 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]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 434:  29%|███▍        | 435/1495 [02:45<07:00,  2.52it/s]
[Running Accuracy]: 0.8138,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 435:  29%|███▏       | 435/1495 [02:45<07:00,  2.52it/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 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 this image under-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image under-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image under-exposure?\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]: 0.8138,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 435:  29%|███▏       | 436/1495 [02:46<08:07,  2.17it/s]
[Running Accuracy]: 0.8142,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 436:  29%|███▏       | 436/1495 [02:46<08:07,  2.17it/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>Is this image under-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 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([-30.7656], 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]: 0.8142,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 436:  29%|███▏       | 437/1495 [02:46<07:19,  2.41it/s]
[Running Accuracy]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 437:  29%|███▏       | 437/1495 [02:46<07:19,  2.41it/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 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 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([-31.4375], 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]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 437:  29%|███▏       | 438/1495 [02:47<06:51,  2.57it/s]
[Running Accuracy]: 0.8151,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 438:  29%|█▊    | 438/1495 [02:47<06:51,  2.57it/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 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>Which part of the image is the focal point?
A. Beach
B. Sea
C. Swimming ring
D. Woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focal point?
A. Beach
B. Sea
C. Swimming ring
D. Woman
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focal point?\nA. Beach\nB. Sea\nC. Swimming ring\nD. Woman\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]: 0.8151,[Response]: A.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 438:  29%|█▊    | 439/1495 [02:47<06:32,  2.69it/s]
[Running Accuracy]: 0.8155,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 439:  29%|██▋      | 439/1495 [02:47<06:32,  2.69it/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>Which part of the image is the focal point?\nA. Beach\nB. Sea\nC. Swimming ring\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 vividity of the image?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color vividity of the image?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the color vividity of the image?\nA. Good\nB. Bad\nC. Fair\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]: 0.8155,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 439:  29%|██▋      | 440/1495 [02:47<06:14,  2.82it/s]
[Running Accuracy]: 0.8136,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 440:  29%|███▏       | 440/1495 [02:47<06:14,  2.82it/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 color vividity of the image?\nA. Good\nB. Bad\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>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([-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]: 0.8136,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 440:  29%|███▏       | 441/1495 [02:48<06:01,  2.91it/s]
[Running Accuracy]: 0.8141,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 441:  29%|███▌        | 441/1495 [02:48<06:01,  2.91it/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>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': 'B.<|endoftext|>'} 

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

prompts: [["Is the face of the fox motion-blurred?\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])
 A.

[Running Accuracy]: 0.8141,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 441:  30%|███▌        | 442/1495 [02:48<05:46,  3.04it/s]
[Running Accuracy]: 0.8145,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 442:  30%|███▎       | 442/1495 [02:48<05:46,  3.04it/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>Is the face of the fox 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>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([-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]: 0.8145,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 442:  30%|███▎       | 443/1495 [02:48<05:48,  3.02it/s]
[Running Accuracy]: 0.8149,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 443:  30%|███▌        | 443/1495 [02:48<05:48,  3.02it/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>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>How clear is this picture?
A. Clear
B. Blurry
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Clear
B. Blurry
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Clear\nB. Blurry\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])
 B.

[Running Accuracy]: 0.8149,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 443:  30%|███▌        | 444/1495 [02:49<07:10,  2.44it/s]
[Running Accuracy]: 0.8153,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 444:  30%|██▍     | 444/1495 [02:49<07:10,  2.44it/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 clear is this picture?\nA. Clear\nB. Blurry\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 overall clarity of this image?
A. High
B. Low
C. Meedium
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. Low
C. Meedium
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. High\nB. Low\nC. Meedium\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]: 0.8153,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 444:  30%|██▍     | 445/1495 [02:49<06:37,  2.64it/s]
[Running Accuracy]: 0.8157,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 445:  30%|███▎       | 445/1495 [02:49<06:37,  2.64it/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 overall clarity of this image?\nA. High\nB. Low\nC. Meedium\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the background in the image?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the background in the image?\nA. Slight\nB. Moderate\nC. Severe\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]: 0.8157,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 445:  30%|███▎       | 446/1495 [02:49<06:24,  2.73it/s]
[Running Accuracy]: 0.8161,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 446:  30%|██▍     | 446/1495 [02:49<06:24,  2.73it/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 blurry is the background in the image?\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>Does the background of the image look grayish?
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 grayish?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the background of the image look grayish?\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]: 0.8161,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 446:  30%|██▍     | 447/1495 [02:50<05:57,  2.93it/s]
[Running Accuracy]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 447:  30%|███▎       | 447/1495 [02:50<05:57,  2.93it/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>Does the background of the image look grayish?\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 feature any repeated elements?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image feature any repeated elements?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image feature any repeated elements?\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]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 447:  30%|███▎       | 448/1495 [02:50<05:53,  2.96it/s]
[Running Accuracy]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 448:  30%|███▎       | 448/1495 [02:50<05:53,  2.96it/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>Does this image feature any repeated elements?\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 in the image is emphasized in the center?
A. Turtle
B. Water surface
C. Grass
D. Leaf on the water surface
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is emphasized in the center?
A. Turtle
B. Water surface
C. Grass
D. Leaf on the water surface
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is emphasized in the center?\nA. Turtle\nB. Water surface\nC. Grass\nD. Leaf on the water surface\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]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 448:  30%|███▎       | 449/1495 [02:50<05:50,  2.98it/s]
[Running Accuracy]: 0.8174,[Response]: A.<|endoftext|>, [Correct Ans]: Turtle, , [Prog]: 449:  30%|██▍     | 449/1495 [02:50<05:50,  2.98it/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>Which object in the image is emphasized in the center?\nA. Turtle\nB. Water surface\nC. Grass\nD. Leaf on the water surface\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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([-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]: 0.8174,[Response]: A.<|endoftext|>, [Correct Ans]: Turtle, , [Prog]: 449:  30%|██▍     | 450/1495 [02:51<05:46,  3.02it/s]
[Running Accuracy]: 0.8178,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 450:  30%|███▎       | 450/1495 [02:51<05:46,  3.02it/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>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 colorful is this picture?
A. Colorful
B. Fair
C. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Fair
C. Dull
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Fair\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])
 A.

[Running Accuracy]: 0.8178,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 450:  30%|███▎       | 451/1495 [02:51<07:15,  2.40it/s]
[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 451:  30%|███       | 451/1495 [02:51<07:15,  2.40it/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 colorful is this picture?\nA. Colorful\nB. Fair\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 most apparent distortion of the humans 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 of the humans 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 of the humans in this image?\nA. Blur\nB. Over-exposure\nC. 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])
 A.

[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 451:  30%|███       | 452/1495 [02:52<06:44,  2.58it/s]
[Running Accuracy]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 452:  30%|███       | 452/1495 [02:52<06:44,  2.58it/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>What is the most apparent distortion of the humans in this image?\nA. Blur\nB. Over-exposure\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 kind of feeling does the image give to people?
A. Dull
B. Dark
C. Restless
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does the image give to people?
A. Dull
B. Dark
C. Restless
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does the image give to people?\nA. Dull\nB. Dark\nC. Restless\nD. Fresh\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]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 452:  30%|███       | 453/1495 [02:52<06:26,  2.69it/s]
[Running Accuracy]: 0.8168,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 453:  30%|██▋      | 453/1495 [02:52<06:26,  2.69it/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>What kind of feeling does the image give to people?\nA. Dull\nB. Dark\nC. Restless\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>Is the woman wearing a black dress 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 woman wearing a black dress the main subject of this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman wearing a black dress the main subject of this image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9062], 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]: 0.8168,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 453:  30%|██▋      | 454/1495 [02:52<06:14,  2.78it/s]
[Running Accuracy]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 454:  30%|███▎       | 454/1495 [02:52<06:14,  2.78it/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>Is the woman wearing a black dress 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>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([-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]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 454:  30%|███▎       | 455/1495 [02:53<05:58,  2.90it/s]
[Running Accuracy]: 0.8176,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 455:  30%|███       | 455/1495 [02:53<05:58,  2.90it/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 composition in 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 image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image rich in color?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image rich in color?\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]: 0.8176,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 455:  31%|███       | 456/1495 [02:53<07:16,  2.38it/s]
[Running Accuracy]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 456:  31%|███▎       | 456/1495 [02:53<07:16,  2.38it/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>Is the 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>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([-31.4062], 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]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 456:  31%|███▎       | 457/1495 [02:54<06:48,  2.54it/s]
[Running Accuracy]: 0.8162,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 457:  31%|███▎       | 457/1495 [02:54<06:48,  2.54it/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 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 clarity of the building acceptable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clarity of the building acceptable?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the clarity of the building acceptable?\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]: 0.8162,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 457:  31%|███▎       | 458/1495 [02:54<07:59,  2.16it/s]
[Running Accuracy]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 458:  31%|███▋        | 458/1495 [02:54<07:59,  2.16it/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>Is the clarity of the building acceptable?\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 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([-31.1562], 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]: 0.8166,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 458:  31%|███▋        | 459/1495 [02:55<07:26,  2.32it/s]
[Running Accuracy]: 0.8148,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 459:  31%|▉  | 459/1495 [02:55<07:26,  2.32it/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 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>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([-30.9688], 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]: 0.8148,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 459:  31%|▉  | 460/1495 [02:55<08:08,  2.12it/s]
[Running Accuracy]: 0.8152,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 460:  31%|███▍       | 460/1495 [02:55<08:08,  2.12it/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>Does this picture have overexposure 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>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([-30.7500], 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]: 0.8152,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 460:  31%|███▍       | 461/1495 [02:55<07:15,  2.38it/s]
[Running Accuracy]: 0.8156,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 461:  31%|███▋        | 461/1495 [02:55<07:15,  2.38it/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>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 lighting of the human in the middle of the 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 the middle of the 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 the middle of the image?\nA. Bright\nB. Medium\nC. Dark\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]: 0.8156,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 461:  31%|███▋        | 462/1495 [02:56<06:49,  2.52it/s]
[Running Accuracy]: 0.8160,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 462:  31%|███       | 462/1495 [02:56<06:49,  2.52it/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 lighting of the human in the middle of the 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 main color tone of the light in the part of the image where the people are?
A. Blue
B. Green
C. Yellow
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the light in the part of the image where the people are?
A. Blue
B. Green
C. Yellow
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the light in the part of the image where the people are?\nA. Blue\nB. Green\nC. Yellow\nD. Red\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])
 D.

[Running Accuracy]: 0.8160,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 462:  31%|███       | 463/1495 [02:56<06:36,  2.60it/s]
[Running Accuracy]: 0.8164,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 463:  31%|███▍       | 463/1495 [02:56<06:36,  2.60it/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>What is the main color tone of the light in the part of the image where the people are?\nA. Blue\nB. Green\nC. Yellow\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 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([-30.4688], 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]: 0.8164,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 463:  31%|███▍       | 464/1495 [02:57<07:34,  2.27it/s]
[Running Accuracy]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 464:  31%|███▍       | 464/1495 [02:57<07:34,  2.27it/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>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 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([-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]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 464:  31%|███▍       | 465/1495 [02:57<06:55,  2.48it/s]
[Running Accuracy]: 0.8172,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 465:  31%|██▍     | 465/1495 [02:57<06:55,  2.48it/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 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 is the most eye-catching color in the image?
A. Red
B. Blue
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most eye-catching color in the image?
A. Red
B. Blue
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.

prompts: [["What is the most eye-catching color in the image?\nA. Red\nB. Blue\nC. Yellow\nD. Brown\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])
 D.

[Running Accuracy]: 0.8172,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 465:  31%|██▍     | 466/1495 [02:57<06:34,  2.61it/s]
[Running Accuracy]: 0.8176,[Response]: D.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 466:  31%|██▊      | 466/1495 [02:57<06:34,  2.61it/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>What is the most eye-catching color in the image?\nA. Red\nB. Blue\nC. Yellow\nD. Brown\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. 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([-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]: 0.8176,[Response]: D.<|endoftext|>, [Correct Ans]: Brown, , [Prog]: 466:  31%|██▊      | 467/1495 [02:58<06:22,  2.69it/s]
[Running Accuracy]: 0.8180,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 467:  31%|███▍       | 467/1495 [02:58<06:22,  2.69it/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 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>Is the cat real in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat real in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat real 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]: 0.8180,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 467:  31%|███▍       | 468/1495 [02:58<06:00,  2.85it/s]
[Running Accuracy]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 468:  31%|███▊        | 468/1495 [02:58<06:00,  2.85it/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>Is the cat 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 is the clarity of the cars in 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 clarity of the cars in this 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 cars in this image?\nA. High\nB. Medium\nC. Low\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]: 0.8184,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 468:  31%|███▊        | 469/1495 [02:59<07:09,  2.39it/s]
[Running Accuracy]: 0.8188,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 469:  31%|███▏      | 469/1495 [02:59<07:09,  2.39it/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 clarity of the cars in this 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 is the brightness level 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 level 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 level of the image?\nA. Low\nB. Medium\nC. High\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]: 0.8188,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 469:  31%|███▏      | 470/1495 [02:59<06:34,  2.60it/s]
[Running Accuracy]: 0.8191,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 470:  31%|███▏      | 470/1495 [02:59<06:34,  2.60it/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 brightness level 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>What distortion is not 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 distortion is not 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 distortion is not 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([-30.8281], 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]: 0.8191,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 470:  32%|███▏      | 471/1495 [02:59<06:00,  2.84it/s]
[Running Accuracy]: 0.8195,[Response]: D<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 471:  32%|▋ | 471/1495 [02:59<06:00,  2.84it/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>What distortion is not 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': '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 woman's face 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 clarity of the woman's face in the image?
A. Good
B. Moderate
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the woman's face in the image?\nA. Good\nB. Moderate\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])
 C.

[Running Accuracy]: 0.8195,[Response]: D<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 471:  32%|▋ | 472/1495 [02:59<05:54,  2.89it/s]
[Running Accuracy]: 0.8178,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 472:  32%|███▏      | 472/1495 [02:59<05:54,  2.89it/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 clarity of the woman's face in the image?\nA. Good\nB. Moderate\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 kind of 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 kind of 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 kind of 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([-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]: 0.8178,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 472:  32%|███▏      | 473/1495 [03:00<05:51,  2.91it/s]
[Running Accuracy]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 473:  32%|▋ | 473/1495 [03:00<05:51,  2.91it/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>Which kind of 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>How clear are the characters on the magazine in this picture?
A. Blurry
B. Fair
C. Clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters on the magazine in this picture?
A. Blurry
B. Fair
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters on the magazine in this picture?\nA. Blurry\nB. Fair\nC. Clear\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]: 0.8182,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 473:  32%|▋ | 474/1495 [03:00<07:14,  2.35it/s]
[Running Accuracy]: 0.8186,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 474:  32%|██▊      | 474/1495 [03:00<07:14,  2.35it/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 clear are the characters on the magazine in this picture?\nA. Blurry\nB. Fair\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 distortion is not in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is not in this picture?
A. Underexposure
B. Motion blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is not in this picture?\nA. Underexposure\nB. Motion blur\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])
 A.

[Running Accuracy]: 0.8186,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 474:  32%|██▊      | 475/1495 [03:01<06:42,  2.54it/s]
[Running Accuracy]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 475:  32%|▉  | 475/1495 [03:01<06:42,  2.54it/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>What distortion is not in this picture?\nA. Underexposure\nB. Motion blur\nC. Overexposure\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 brightness of 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 brightness of the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the image?\nA. High\nB. Low\nC. Medium\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]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 475:  32%|▉  | 476/1495 [03:01<06:17,  2.70it/s]
[Running Accuracy]: 0.8151,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 476:  32%|██▌     | 476/1495 [03:01<06:17,  2.70it/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 brightness of the 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>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([-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]: 0.8151,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 476:  32%|██▌     | 477/1495 [03:01<06:06,  2.78it/s]
[Running Accuracy]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 477:  32%|███▊        | 477/1495 [03:01<06:06,  2.78it/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>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>Which part of the image get over-exposed?
A. The grassland
B. The sky
C. The building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image get over-exposed?
A. The grassland
B. The sky
C. The building
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image get over-exposed?\nA. The grassland\nB. The sky\nC. The building\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]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 477:  32%|███▊        | 478/1495 [03:02<06:25,  2.64it/s]
[Running Accuracy]: 0.8138,[Response]: B.<|endoftext|>, [Correct Ans]: The sky, , [Prog]: 478:  32%|██▏    | 478/1495 [03:02<06:25,  2.64it/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>Which part of the image get over-exposed?\nA. The grassland\nB. The sky\nC. The 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>Where is the focus of this picture?
A. Front
B. Back
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Front
B. Back
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Front\nB. Back\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]: 0.8138,[Response]: B.<|endoftext|>, [Correct Ans]: The sky, , [Prog]: 478:  32%|██▏    | 479/1495 [03:02<06:12,  2.73it/s]
[Running Accuracy]: 0.8142,[Response]: A.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 479:  32%|██▉      | 479/1495 [03:02<06:12,  2.73it/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>Where is the focus of this picture?\nA. Front\nB. Back\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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. audience
B. stage
C. singer
D. spotlight
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. audience
B. stage
C. singer
D. spotlight
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. audience\nB. stage\nC. singer\nD. spotlight\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]: 0.8142,[Response]: A.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 479:  32%|██▉      | 480/1495 [03:03<06:04,  2.78it/s]
[Running Accuracy]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: singer, , [Prog]: 480:  32%|██▌     | 480/1495 [03:03<06:04,  2.78it/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>In the composition of the image, which object is emphasized in the center?\nA. audience\nB. stage\nC. singer\nD. spotlight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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([-30.8906], 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]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: singer, , [Prog]: 480:  32%|██▌     | 481/1495 [03:03<06:07,  2.76it/s]
[Running Accuracy]: 0.8150,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 481:  32%|███▌       | 481/1495 [03:03<06:07,  2.76it/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>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>Is there an issue of 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 an issue of excessive noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there an issue of excessive noise 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]: 0.8150,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 481:  32%|███▌       | 482/1495 [03:03<05:59,  2.82it/s]
[Running Accuracy]: 0.8154,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 482:  32%|███▊        | 482/1495 [03:03<05:59,  2.82it/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>Is there an issue of excessive 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>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([-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]: 0.8154,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 482:  32%|███▉        | 483/1495 [03:04<07:16,  2.32it/s]
[Running Accuracy]: 0.8157,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 483:  32%|███▌       | 483/1495 [03:04<07:16,  2.32it/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>Does this picture 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 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([-31.3281], 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]: 0.8157,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 483:  32%|███▌       | 484/1495 [03:04<08:06,  2.08it/s]
[Running Accuracy]: 0.8161,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 484:  32%|███▌       | 484/1495 [03:04<08:06,  2.08it/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>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 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([-31.2656], 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]: 0.8161,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 484:  32%|███▌       | 485/1495 [03:05<07:19,  2.30it/s]
[Running Accuracy]: 0.8165,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 485:  32%|███▉        | 485/1495 [03:05<07:19,  2.30it/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>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 of the background cloth in this image?
A. Monotonous
B. Moderate
C. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the background cloth in this image?
A. Monotonous
B. Moderate
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the background cloth in this image?\nA. Monotonous\nB. Moderate\nC. Vibrant\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]: 0.8165,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 485:  33%|███▉        | 486/1495 [03:05<06:45,  2.49it/s]
[Running Accuracy]: 0.8169,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 486:  33%|██▎    | 486/1495 [03:05<06:45,  2.49it/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 color of the background cloth in this image?\nA. Monotonous\nB. Moderate\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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 child's top vivid in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the child's top vivid in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the child's top vivid in this picture?\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]: 0.8169,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 486:  33%|██▎    | 487/1495 [03:05<06:26,  2.61it/s]
[Running Accuracy]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 487:  33%|███▌       | 487/1495 [03:05<06:26,  2.61it/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>Is the color of the child's top vivid 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>Is the bicycle clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bicycle clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the bicycle clear 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])
 A.

[Running Accuracy]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 487:  33%|███▌       | 488/1495 [03:06<06:11,  2.71it/s]
[Running Accuracy]: 0.8176,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 488:  33%|███▌       | 488/1495 [03:06<06:11,  2.71it/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>Is the bicycle 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 would you rate 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 would you rate the clarity 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 clarity of this image?\nA. Medium\nB. Low\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]: 0.8176,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 488:  33%|███▌       | 489/1495 [03:06<06:10,  2.71it/s]
[Running Accuracy]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 489:  33%|███▌       | 489/1495 [03:06<06:10,  2.71it/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 would you rate 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>Is the sky affected by over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky affected by over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky affected by over-exposure?\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. Yes

[Running Accuracy]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 489:  33%|███▌       | 490/1495 [03:07<07:07,  2.35it/s]
[Running Accuracy]: 0.8184,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 490:  33%|██▎    | 490/1495 [03:07<07:07,  2.35it/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>Is the sky affected by over-exposure?\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 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([-30.7969], 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]: 0.8184,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 490:  33%|██▎    | 491/1495 [03:07<06:32,  2.55it/s]
[Running Accuracy]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 491:  33%|██▋     | 491/1495 [03:07<06:32,  2.55it/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 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 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([-31.0469], 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]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 491:  33%|██▋     | 492/1495 [03:08<07:33,  2.21it/s]
[Running Accuracy]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 492:  33%|███▉        | 492/1495 [03:08<07:33,  2.21it/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>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 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([-30.2188], 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]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 492:  33%|███▉        | 493/1495 [03:08<06:53,  2.42it/s]
[Running Accuracy]: 0.8195,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 493:  33%|███▋       | 493/1495 [03:08<06:53,  2.42it/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 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 lightsource of the image?
A. Sunlight
B. Streetlight
C. Reflection
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main lightsource of the image?
A. Sunlight
B. Streetlight
C. Reflection
Answer with the option's letter from the given choices directly.

prompts: [["What is the main lightsource of the image?\nA. Sunlight\nB. Streetlight\nC. Reflection\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]: 0.8195,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 493:  33%|███▋       | 494/1495 [03:08<06:28,  2.57it/s]
[Running Accuracy]: 0.8198,[Response]: A.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 494:  33%|█▉    | 494/1495 [03:08<06:28,  2.57it/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>What is the main lightsource of the image?\nA. Sunlight\nB. Streetlight\nC. Reflection\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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([-31.1562], 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]: 0.8198,[Response]: A.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 494:  33%|█▉    | 495/1495 [03:09<06:05,  2.74it/s]
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 495:  33%|███▋       | 495/1495 [03:09<06:05,  2.74it/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>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>Which object in the image is affected by slight motion blur?
A. The grass
B. The trees
C. The barricade
D. The man on the skateboard
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. The grass
B. The trees
C. The barricade
D. The man on the skateboard
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is affected by slight motion blur?\nA. The grass\nB. The trees\nC. The barricade\nD. The man on the skateboard\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]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 495:  33%|███▋       | 496/1495 [03:09<05:48,  2.87it/s]
[Running Accuracy]: 0.8185,[Response]: D.<|endoftext|>, [Correct Ans]: The man on the skateboard, , [Prog]: 496:  33%|▎| 496/1495 [03:09<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>Which object in the image is affected by slight motion blur?\nA. The grass\nB. The trees\nC. The barricade\nD. The man on the skateboard\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([-31.4375], 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]: 0.8185,[Response]: D.<|endoftext|>, [Correct Ans]: The man on the skateboard, , [Prog]: 496:  33%|▎| 497/1495 [03:09<05:36
[Running Accuracy]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 497:  33%|███▋       | 497/1495 [03:09<05:36,  2.96it/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>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>Are the signs in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the signs in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the signs in this 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])
 A.

[Running Accuracy]: 0.8189,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 497:  33%|███▋       | 498/1495 [03:09<05:32,  3.00it/s]
[Running Accuracy]: 0.8193,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 498:  33%|███▉        | 498/1495 [03:10<05:32,  3.00it/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>Are the signs 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>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([-31.4219], 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]: 0.8193,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 498:  33%|████        | 499/1495 [03:10<05:30,  3.01it/s]
[Running Accuracy]: 0.8196,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 499:  33%|███▋       | 499/1495 [03:10<05:30,  3.01it/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>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>Which quality issue is the most severe in the image?
A. Motion blur
B. Distortion
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality issue is the most severe in the image?
A. Motion blur
B. Distortion
C. Overexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue is the most severe in the image?\nA. Motion blur\nB. Distortion\nC. Overexposure\nD. Out of focus\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]: 0.8196,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 499:  33%|███▋       | 500/1495 [03:10<05:38,  2.94it/s]
[Running Accuracy]: 0.8200,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 500:  33%|▋ | 500/1495 [03:10<05:38,  2.94it/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>Which quality issue is the most severe in the image?\nA. Motion blur\nB. Distortion\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>How is the exposure like for the window in this image?
A. Appropriate
B. Under-exposure
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure like for the window in this image?
A. Appropriate
B. Under-exposure
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure like for the window in this image?\nA. Appropriate\nB. Under-exposure\nC. Over-exposure\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]: 0.8200,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 500:  34%|▋ | 501/1495 [03:10<05:29,  3.02it/s]
[Running Accuracy]: 0.8204,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 501:  34%|▎| 501/1495 [03:11<05:29,  3.02it/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 exposure like for the window in this image?\nA. Appropriate\nB. Under-exposure\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 clear is 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 image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How clear is 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])
 C.

[Running Accuracy]: 0.8204,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 501:  34%|▎| 502/1495 [03:11<05:32,  2.98it/s]
[Running Accuracy]: 0.8187,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 502:  34%|███      | 502/1495 [03:11<05:32,  2.98it/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 clear is the image?\nA. Clear\nB. Blurry\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>Where is the brightest part about the image?
A. The wall
B. Eye and mouth of the pumpkin
C. Rest of the pumpkin
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the brightest part about the image?
A. The wall
B. Eye and mouth of the pumpkin
C. Rest of the pumpkin
Answer with the option's letter from the given choices directly.

prompts: [["Where is the brightest part about the image?\nA. The wall\nB. Eye and mouth of the pumpkin\nC. Rest of the pumpkin\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]: 0.8187,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 502:  34%|███      | 503/1495 [03:11<05:33,  2.97it/s]
[Running Accuracy]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: Eye and mouth of the pumpkin, , [Prog]: 503:  34%|▎| 503/1495 [03:11<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>Where is the brightest part about the image?\nA. The wall\nB. Eye and mouth of the pumpkin\nC. Rest of the pumpkin\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 suffer from?
A. Blur
B. Noise
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion does this image suffer from?
A. Blur
B. Noise
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion does this image suffer from?\nA. Blur\nB. Noise\nC. Underexposure\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]: 0.8191,[Response]: B.<|endoftext|>, [Correct Ans]: Eye and mouth of the pumpkin, , [Prog]: 503:  34%|▎| 504/1495 [03:12<05
[Running Accuracy]: 0.8194,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 504:  34%|███▎      | 504/1495 [03:12<05:31,  2.99it/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>What kind of distortion does this image suffer from?\nA. Blur\nB. Noise\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>What quality issues exist in the image?
A. Overexposure
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What quality issues exist in the image?
A. Overexposure
B. Motion blur
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What quality issues exist in the image?\nA. Overexposure\nB. Motion blur\nC. Noise\nD. 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]: 0.8194,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 504:  34%|███▍      | 505/1495 [03:12<05:28,  3.01it/s]
[Running Accuracy]: 0.8178,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 505:  34%|███      | 505/1495 [03:12<05:28,  3.01it/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>What quality issues exist in the image?\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 ball 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 ball 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 ball in this image?\nA. Monotonous\nB. Vibrant\nC. Average\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]: 0.8178,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 505:  34%|███      | 506/1495 [03:12<05:29,  3.00it/s]
[Running Accuracy]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 506:  34%|██▎    | 506/1495 [03:12<05:29,  3.00it/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 color of the ball 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>How blurry is the background room in 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 room in 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 room in the image?\nA. Moderate\nB. Slight\nC. Severe\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]: 0.8182,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 506:  34%|██▎    | 507/1495 [03:12<05:25,  3.03it/s]
[Running Accuracy]: 0.8185,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 507:  34%|██▋     | 507/1495 [03:12<05:25,  3.03it/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 blurry is the background room in 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>What is the major distortion that happens in the image?
A. Overexposure
B. Blurriness
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the major distortion that happens in the image?
A. Overexposure
B. Blurriness
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion that happens in the image?\nA. Overexposure\nB. Blurriness\nC. Noise\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]: 0.8185,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 507:  34%|██▋     | 508/1495 [03:13<05:20,  3.08it/s]
[Running Accuracy]: 0.8189,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 508:  34%|███      | 508/1495 [03:13<05:20,  3.08it/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>What is the major distortion that happens in the image?\nA. Overexposure\nB. Blurriness\nC. 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 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([-31.1406], 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]: 0.8189,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 508:  34%|███      | 509/1495 [03:13<05:24,  3.04it/s]
[Running Accuracy]: 0.8173,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 509:  34%|██▋     | 509/1495 [03:13<05:24,  3.04it/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 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>How would you rate 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 would you rate the clarity of 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 this image?\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])
 A.

[Running Accuracy]: 0.8173,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 509:  34%|██▋     | 510/1495 [03:14<05:42,  2.87it/s]
[Running Accuracy]: 0.8157,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 510:  34%|███▊       | 510/1495 [03:14<05:42,  2.87it/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 would you rate 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 bull clear in the picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bull clear in the picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the bull clear in the picture?\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]: 0.8157,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 510:  34%|███▊       | 511/1495 [03:14<05:35,  2.94it/s]
[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 511:  34%|███▊       | 511/1495 [03:14<05:35,  2.94it/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>Is the bull clear in the 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>Is there a problem of 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 a problem of excessive noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there a problem of excessive noise in the 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]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 511:  34%|███▊       | 512/1495 [03:14<05:31,  2.96it/s]
[Running Accuracy]: 0.8164,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 512:  34%|████        | 512/1495 [03:14<05:31,  2.96it/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>Is there a problem of 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>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([-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]: 0.8164,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 512:  34%|████        | 513/1495 [03:15<06:38,  2.46it/s]
[Running Accuracy]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 513:  34%|███▊       | 513/1495 [03:15<06:38,  2.46it/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>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>Which color is the brightest in this image?
A. Blue
B. Brown
C. Red
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the brightest in this image?
A. Blue
B. Brown
C. Red
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the brightest in this image?\nA. Blue\nB. Brown\nC. Red\nD. Black\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]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 513:  34%|███▊       | 514/1495 [03:15<06:13,  2.63it/s]
[Running Accuracy]: 0.8171,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 514:  34%|███▍      | 514/1495 [03:15<06:13,  2.63it/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>Which color is the brightest in this image?\nA. Blue\nB. Brown\nC. Red\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>How rich is the color of the image?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color of the image?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color of the image?\nA. Monotonous\nB. Rich\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])
 B.

[Running Accuracy]: 0.8171,[Response]: A.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 514:  34%|███▍      | 515/1495 [03:15<05:53,  2.77it/s]
[Running Accuracy]: 0.8155,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 515:  34%|█▍  | 515/1495 [03:15<05:53,  2.77it/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 rich is the color of the image?\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>How good is the composition of this picture?
A. Good
B. Poor
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. Poor
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. Poor\nC. Fair\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]: 0.8155,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 515:  35%|█▍  | 516/1495 [03:16<05:40,  2.88it/s]
[Running Accuracy]: 0.8159,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 516:  35%|███▍      | 516/1495 [03:16<05:40,  2.88it/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 good is the composition of this picture?\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>Which color is the brightest in this image?
A. Black
B. White
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the brightest in this image?
A. Black
B. White
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the brightest in this image?\nA. Black\nB. White\nC. Yellow\nD. Brown\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]: 0.8159,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 516:  35%|███▍      | 517/1495 [03:16<05:33,  2.94it/s]
[Running Accuracy]: 0.8162,[Response]: C.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 517:  35%|██▊     | 517/1495 [03:16<05:33,  2.94it/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>Which color is the brightest in this image?\nA. Black\nB. White\nC. Yellow\nD. Brown\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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. 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. Noise
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. Noise\nC. Motion blur\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])
 C.

[Running Accuracy]: 0.8162,[Response]: C.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 517:  35%|██▊     | 518/1495 [03:16<05:24,  3.01it/s]
[Running Accuracy]: 0.8166,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 518:  35%|█  | 518/1495 [03:16<05:24,  3.01it/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>What is the major distortion of 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>Which reason is not a cause of low perceptual quality of this image?
A. Underexposure
B. Chaotic view
C. Blurriness
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which reason is not a cause of low perceptual quality of this image?
A. Underexposure
B. Chaotic view
C. Blurriness
Answer with the option's letter from the given choices directly.

prompts: [["Which reason is not a cause of low perceptual quality of this image?\nA. Underexposure\nB. Chaotic view\nC. Blurriness\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]: 0.8166,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 518:  35%|█  | 519/1495 [03:17<05:19,  3.05it/s]
[Running Accuracy]: 0.8170,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 519:  35%|▎| 519/1495 [03:17<05:19,  3.05it/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>Which reason is not a cause of low perceptual quality of this image?\nA. Underexposure\nB. Chaotic view\nC. Blurriness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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 vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color vibrant?\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]: 0.8170,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 519:  35%|▎| 520/1495 [03:17<05:14,  3.10it/s]
[Running Accuracy]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 520:  35%|████▏       | 520/1495 [03:17<05:14,  3.10it/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>Is the image color 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 clear is 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 image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Poor\nB. Good\nC. Average\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]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 520:  35%|████▏       | 521/1495 [03:17<05:14,  3.09it/s]
[Running Accuracy]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 521:  35%|███▍      | 521/1495 [03:17<05:14,  3.09it/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 clear is 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>Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\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]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 521:  35%|███▍      | 522/1495 [03:18<05:14,  3.10it/s]
[Running Accuracy]: 0.8161,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 522:  35%|████▏       | 522/1495 [03:18<05:14,  3.10it/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>Does this picture have underexposure 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>What is emphasized in the center of this picture?
A. Crowd
B. Traffic light
C. Car
D. Bus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Crowd
B. Traffic light
C. Car
D. Bus
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Crowd\nB. Traffic light\nC. Car\nD. Bus\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]: 0.8161,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 522:  35%|████▏       | 523/1495 [03:18<05:10,  3.13it/s]
[Running Accuracy]: 0.8164,[Response]: D.<|endoftext|>, [Correct Ans]: Bus, , [Prog]: 523:  35%|███▊       | 523/1495 [03:18<05:10,  3.13it/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>What is emphasized in the center of this picture?\nA. Crowd\nB. Traffic light\nC. Car\nD. Bus\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 are present in the image?
A. Overexposure
B. OutOfFocus
C. Backlighting
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems are present in the image?
A. Overexposure
B. OutOfFocus
C. Backlighting
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems are present in the image?\nA. Overexposure\nB. OutOfFocus\nC. Backlighting\nD. Underexposure\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]: 0.8164,[Response]: D.<|endoftext|>, [Correct Ans]: Bus, , [Prog]: 523:  35%|███▊       | 524/1495 [03:18<05:16,  3.07it/s]
[Running Accuracy]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 524:  35%|▋ | 524/1495 [03:18<05:16,  3.07it/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>What problems are present in the image?\nA. Overexposure\nB. OutOfFocus\nC. Backlighting\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 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([-31.0938], 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]: 0.8168,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 524:  35%|▋ | 525/1495 [03:19<05:21,  3.02it/s]
[Running Accuracy]: 0.8171,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 525:  35%|███▊       | 525/1495 [03:19<05:21,  3.02it/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>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>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([-31.0781], 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]: 0.8171,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 525:  35%|███▊       | 526/1495 [03:19<05:11,  3.11it/s]
[Running Accuracy]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 526:  35%|████▏       | 526/1495 [03:19<05:11,  3.11it/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>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': 'A.<|endoftext|>'} 

prompt A chat between 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. Overexposure
B. Noise
C. Underexposure
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. Overexposure
B. Noise
C. Underexposure
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. Overexposure\nB. Noise\nC. Underexposure\nD. Out of focus\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]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 526:  35%|████▏       | 527/1495 [03:19<05:12,  3.09it/s]
[Running Accuracy]: 0.8178,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 527:  35%|▎| 527/1495 [03:19<05:12,  3.09it/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>Which of the following image quality issues does this image NOT have?\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>Which object is emphasized in the center in the composition of the image?
A. Trees
B. Sea waves
C. Beach
D. People and horses
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center in the composition of the image?
A. Trees
B. Sea waves
C. Beach
D. People and horses
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center in the composition of the image?\nA. Trees\nB. Sea waves\nC. Beach\nD. People and horses\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])
 D.

[Running Accuracy]: 0.8178,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 527:  35%|▎| 528/1495 [03:20<05:19,  3.03it/s]
[Running Accuracy]: 0.8182,[Response]: D.<|endoftext|>, [Correct Ans]: People and horses, , [Prog]: 528:  35%|▎| 528/1495 [03:20<05:19,  3.03i
 {'prompt': "A chat between 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 in the composition of the image?\nA. Trees\nB. Sea waves\nC. Beach\nD. People and horses\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 colorful isthis picture?
A. Dull
B. Colorful
C. Normal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful isthis picture?
A. Dull
B. Colorful
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How colorful isthis picture?\nA. Dull\nB. Colorful\nC. Normal\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]: 0.8182,[Response]: D.<|endoftext|>, [Correct Ans]: People and horses, , [Prog]: 528:  35%|▎| 529/1495 [03:20<05:24,  2.97i
[Running Accuracy]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 529:  35%|███▌      | 529/1495 [03:20<05:24,  2.97it/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 colorful isthis picture?\nA. Dull\nB. Colorful\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 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([-31.0781], 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]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 529:  35%|███▌      | 530/1495 [03:20<05:13,  3.08it/s]
[Running Accuracy]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 530:  35%|███▉       | 530/1495 [03:20<05:13,  3.08it/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>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>In the composition example of the image, which image is emphasized in the center?
A. Grass
B. House
C. Trees
D. Child
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition example of the image, which image is emphasized in the center?
A. Grass
B. House
C. Trees
D. Child
Answer with the option's letter from the given choices directly.

prompts: [["In the composition example of the image, which image is emphasized in the center?\nA. Grass\nB. House\nC. Trees\nD. Child\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]: 0.8170,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 530:  36%|███▉       | 531/1495 [03:21<04:59,  3.22it/s]
[Running Accuracy]: 0.8173,[Response]: D.<|endoftext|>, [Correct Ans]: Child, , [Prog]: 531:  36%|███▏     | 531/1495 [03:21<04:59,  3.22it/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>In the composition example of the image, which image is emphasized in the center?\nA. Grass\nB. House\nC. Trees\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>Is the puppy clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the puppy clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the puppy clear 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]: 0.8173,[Response]: D.<|endoftext|>, [Correct Ans]: Child, , [Prog]: 531:  36%|███▏     | 532/1495 [03:21<05:01,  3.20it/s]
[Running Accuracy]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 532:  36%|███▉       | 532/1495 [03:21<05:01,  3.20it/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>Is the puppy 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>Does this image suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image suffer from over-exposure?\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]: 0.8177,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 532:  36%|███▉       | 533/1495 [03:21<05:07,  3.13it/s]
[Running Accuracy]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 533:  36%|███▉       | 533/1495 [03:21<05:07,  3.13it/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>Does this image 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 of the zebra in the right 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 zebra in the right 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 zebra in the right in this image?\nA. Bright\nB. Medium\nC. Dark\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]: 0.8180,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 533:  36%|███▉       | 534/1495 [03:21<05:04,  3.15it/s]
[Running Accuracy]: 0.8184,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 534:  36%|███▌      | 534/1495 [03:21<05:04,  3.15it/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 lighting of the zebra in the right 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>Is the hot air balloon rich in color in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the hot air balloon rich in color in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the hot air balloon rich in color in this 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])
 B.

[Running Accuracy]: 0.8184,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 534:  36%|███▌      | 535/1495 [03:22<04:58,  3.22it/s]
[Running Accuracy]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 535:  36%|███▉       | 535/1495 [03:22<04:58,  3.22it/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>Is the hot air balloon rich in color 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 problem does the mannequin suffers most?
A. Compression Artifacts
B. Noise
C. Blur
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problem does the mannequin suffers most?
A. Compression Artifacts
B. Noise
C. Blur
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problem does the mannequin suffers most?\nA. Compression Artifacts\nB. Noise\nC. Blur\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]: 0.8187,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 535:  36%|███▉       | 536/1495 [03:22<06:24,  2.50it/s]
[Running Accuracy]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 536:  36%|███▌      | 536/1495 [03:22<06:24,  2.50it/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>What problem does the mannequin suffers most?\nA. Compression Artifacts\nB. Noise\nC. Blur\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>Which can be used to describe the composition of the image?
A. Symmetrical
B. Unbalanced
C. Tilted
D. Chaotic
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which can be used to describe the composition of the image?
A. Symmetrical
B. Unbalanced
C. Tilted
D. Chaotic
Answer with the option's letter from the given choices directly.

prompts: [["Which can be used to describe the composition of the image?\nA. Symmetrical\nB. Unbalanced\nC. Tilted\nD. Chaotic\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]: 0.8172,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 536:  36%|███▌      | 537/1495 [03:23<06:06,  2.61it/s]
[Running Accuracy]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 537:  36%|█  | 537/1495 [03:23<06:06,  2.61it/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>Which can be used to describe the composition of the image?\nA. Symmetrical\nB. Unbalanced\nC. Tilted\nD. Chaotic\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 bears 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 two bears in focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the two bears in focus in this picture?\nA. Yes\nB. No\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]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Symmetrical, , [Prog]: 537:  36%|█  | 538/1495 [03:23<05:33,  2.87it/s]
[Running Accuracy]: 0.8178,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 538:  36%|████▎       | 538/1495 [03:23<05:33,  2.87it/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>Are the two bears 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>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([-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]: 0.8178,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 538:  36%|████▎       | 539/1495 [03:23<05:34,  2.86it/s]
[Running Accuracy]: 0.8163,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 539:  36%|██▉     | 539/1495 [03:23<05:34,  2.86it/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 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': 'B.<|endoftext|>'} 

prompt A chat between 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. Overexposure
B. Motion blur
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is not present in this image?
A. Overexposure
B. Motion blur
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is not present in this image?\nA. Overexposure\nB. Motion blur\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]: 0.8163,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 539:  36%|██▉     | 540/1495 [03:24<07:15,  2.19it/s]
[Running Accuracy]: 0.8167,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 540:  36%|▎| 540/1495 [03:24<07:15,  2.19it/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>What distortion is not present in this image?\nA. Overexposure\nB. Motion 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>Is the clarity of this image very high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the clarity of this image very high?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the clarity of this image very 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])
 A.

[Running Accuracy]: 0.8167,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 540:  36%|▎| 541/1495 [03:24<06:49,  2.33it/s]
[Running Accuracy]: 0.8170,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 541:  36%|████▎       | 541/1495 [03:24<06:49,  2.33it/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>Is the clarity of this image very high?\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 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([-31.3281], 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]: 0.8170,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 541:  36%|████▎       | 542/1495 [03:25<06:18,  2.52it/s]
[Running Accuracy]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 542:  36%|███▉       | 542/1495 [03:25<06:18,  2.52it/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>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>How is the lighting in the background?
A. Extremely Dark
B. Relatively Bright
C. Extremely Bright
D. Relatively Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting in the background?
A. Extremely Dark
B. Relatively Bright
C. Extremely Bright
D. Relatively Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting in the background?\nA. Extremely Dark\nB. Relatively Bright\nC. Extremely Bright\nD. Relatively 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])
 D.

[Running Accuracy]: 0.8173,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 542:  36%|███▉       | 543/1495 [03:25<05:53,  2.69it/s]
[Running Accuracy]: 0.8177,[Response]: D.<|endoftext|>, [Correct Ans]: Relatively Dark, , [Prog]: 543:  36%|▎| 543/1495 [03:25<05:53,  2.69it/
 {'prompt': "A chat between a curious 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 in the background?\nA. Extremely Dark\nB. Relatively Bright\nC. Extremely Bright\nD. Relatively 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>Which object in the image is emphasized in the center?
A. Television
B. Bed
C. Kitten
D. Books
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is emphasized in the center?
A. Television
B. Bed
C. Kitten
D. Books
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is emphasized in the center?\nA. Television\nB. Bed\nC. Kitten\nD. Books\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]: 0.8177,[Response]: D.<|endoftext|>, [Correct Ans]: Relatively Dark, , [Prog]: 543:  36%|▎| 544/1495 [03:25<05:42,  2.77it/
[Running Accuracy]: 0.8180,[Response]: C.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 544:  36%|██▉     | 544/1495 [03:25<05:42,  2.77it/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>Which object in the image is emphasized in the center?\nA. Television\nB. Bed\nC. Kitten\nD. Books\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. person
B. dog
C. television
D. chair
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. person
B. dog
C. television
D. chair
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. person\nB. dog\nC. television\nD. chair\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]: 0.8180,[Response]: C.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 544:  36%|██▉     | 545/1495 [03:26<05:31,  2.87it/s]
[Running Accuracy]: 0.8183,[Response]: B.<|endoftext|>, [Correct Ans]: dog, , [Prog]: 545:  36%|████       | 545/1495 [03:26<05:31,  2.87it/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>Which object is emphasized in the composition of the image?\nA. person\nB. dog\nC. television\nD. chair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 the brightest?
A. Stage
B. Screen
C. Audience
D. Speaker
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image looks the brightest?
A. Stage
B. Screen
C. Audience
D. Speaker
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image looks the brightest?\nA. Stage\nB. Screen\nC. Audience\nD. Speaker\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]: 0.8183,[Response]: B.<|endoftext|>, [Correct Ans]: dog, , [Prog]: 545:  37%|████       | 546/1495 [03:26<05:25,  2.92it/s]
[Running Accuracy]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Speaker, , [Prog]: 546:  37%|██▌    | 546/1495 [03:26<05:25,  2.92it/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>Which object in the image looks the brightest?\nA. Stage\nB. Screen\nC. Audience\nD. Speaker\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man in this image clear?\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]: 0.8168,[Response]: B.<|endoftext|>, [Correct Ans]: Speaker, , [Prog]: 546:  37%|██▌    | 547/1495 [03:26<05:17,  2.99it/s]
[Running Accuracy]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 547:  37%|████       | 547/1495 [03:26<05:17,  2.99it/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>Is the man 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>Is there any content twist in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any content twist in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any content twist in this 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]: 0.8172,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 547:  37%|████       | 548/1495 [03:27<06:27,  2.45it/s]
[Running Accuracy]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 548:  37%|████       | 548/1495 [03:27<06:27,  2.45it/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>Is there any content twist 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 image of high contrast?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image of high contrast?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image of high contrast?\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]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 548:  37%|████       | 549/1495 [03:27<05:56,  2.65it/s]
[Running Accuracy]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 549:  37%|████▍       | 549/1495 [03:27<05:56,  2.65it/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>Is this image of high contrast?\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 vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color vibrant?\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]: 0.8179,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 549:  37%|████▍       | 550/1495 [03:28<05:35,  2.82it/s]
[Running Accuracy]: 0.8182,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 550:  37%|████▍       | 550/1495 [03:28<05:35,  2.82it/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>Is the image color 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>Is the image color vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image color vibrant?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image color vibrant?\nA. Yes\nB. No\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]: 0.8182,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 550:  37%|████▍       | 551/1495 [03:28<05:24,  2.91it/s]
[Running Accuracy]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 551:  37%|████       | 551/1495 [03:28<05:24,  2.91it/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>Is the image color 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 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([-30.3281], 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]: 0.8185,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 551:  37%|████       | 552/1495 [03:28<05:19,  2.95it/s]
[Running Accuracy]: 0.8188,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 552:  37%|████       | 552/1495 [03:28<05:19,  2.95it/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 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 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 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 saturation of this image?\nA. High\nB. Low\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0625], 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]: 0.8188,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 552:  37%|████       | 553/1495 [03:29<05:31,  2.84it/s]
[Running Accuracy]: 0.8192,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 553:  37%|████       | 553/1495 [03:29<05:31,  2.84it/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 saturation 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 object in the image is severely affected by motion blur?
A. Athlete
B. Signboard
C. Spectators
D. Railing
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. Athlete
B. Signboard
C. Spectators
D. Railing
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is severely affected by motion blur?\nA. Athlete\nB. Signboard\nC. Spectators\nD. Railing\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]: 0.8192,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 553:  37%|████       | 554/1495 [03:29<05:21,  2.92it/s]
[Running Accuracy]: 0.8195,[Response]: A.<|endoftext|>, [Correct Ans]: Athlete, , [Prog]: 554:  37%|██▌    | 554/1495 [03:29<05:21,  2.92it/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>Which object in the image is severely affected by motion blur?\nA. Athlete\nB. Signboard\nC. Spectators\nD. Railing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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([-31.3594], 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]: 0.8195,[Response]: A.<|endoftext|>, [Correct Ans]: Athlete, , [Prog]: 554:  37%|██▌    | 555/1495 [03:29<05:19,  2.94it/s]
[Running Accuracy]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 555:  37%|████▍       | 555/1495 [03:29<05:19,  2.94it/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>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 major distortion of the noodles 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 noodles 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 noodles 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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 C.

[Running Accuracy]: 0.8180,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 555:  37%|████▍       | 556/1495 [03:30<05:06,  3.06it/s]
[Running Accuracy]: 0.8183,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 556:  37%|███▋      | 556/1495 [03:30<05:06,  3.06it/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>What is the major distortion of the noodles 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>Is this image aesthetically pleasing?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically pleasing?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically pleasing?\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]: 0.8183,[Response]: C.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 556:  37%|███▋      | 557/1495 [03:30<05:06,  3.06it/s]
[Running Accuracy]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 557:  37%|████       | 557/1495 [03:30<05:06,  3.06it/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>Is this image aesthetically pleasing?\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 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([-31.3750], 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]: 0.8187,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 557:  37%|████       | 558/1495 [03:30<05:00,  3.12it/s]
[Running Accuracy]: 0.8190,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 558:  37%|████       | 558/1495 [03:30<05:00,  3.12it/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>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>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([-30.9531], 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]: 0.8190,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 558:  37%|████       | 559/1495 [03:30<05:02,  3.09it/s]
[Running Accuracy]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 559:  37%|██▉     | 559/1495 [03:30<05:02,  3.09it/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 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>Is there any glare in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any glare in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any glare in the image?\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]: 0.8175,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 559:  37%|██▉     | 560/1495 [03:31<06:13,  2.51it/s]
[Running Accuracy]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 560:  37%|████       | 560/1495 [03:31<06:13,  2.51it/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>Is there any glare 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>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([-31.1094], 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]: 0.8179,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 560:  38%|████▏      | 561/1495 [03:31<05:53,  2.64it/s]
[Running Accuracy]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 561:  38%|████▏      | 561/1495 [03:31<05:53,  2.64it/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>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': 'A.<|endoftext|>'} 

prompt A chat between 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([-31.0156], 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]: 0.8164,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 561:  38%|████▏      | 562/1495 [03:32<05:32,  2.81it/s]
[Running Accuracy]: 0.8149,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 562:  38%|████▏      | 562/1495 [03:32<05:32,  2.81it/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>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>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([-30.9375], 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]: 0.8149,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 562:  38%|████▏      | 563/1495 [03:32<05:15,  2.96it/s]
[Running Accuracy]: 0.8135,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 563:  38%|████▌       | 563/1495 [03:32<05:15,  2.96it/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>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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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([-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]: 0.8135,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 563:  38%|████▌       | 564/1495 [03:32<05:07,  3.03it/s]
[Running Accuracy]: 0.8121,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 564:  38%|███▊      | 564/1495 [03:32<05:07,  3.03it/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 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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 for 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 for 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 for this picture?\nA. Low\nB. Medium\nC. High\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]: 0.8121,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 564:  38%|███▊      | 565/1495 [03:33<05:05,  3.05it/s]
[Running Accuracy]: 0.8124,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 565:  38%|████▏      | 565/1495 [03:33<05:05,  3.05it/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 quality for 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>Is the sky in this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky in this picture bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky in this picture bright?\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]: 0.8124,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 565:  38%|████▏      | 566/1495 [03:33<06:11,  2.50it/s]
[Running Accuracy]: 0.8127,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 566:  38%|████▌       | 566/1495 [03:33<06:11,  2.50it/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>Is the sky in 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>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([-30.7500], 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]: 0.8127,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 566:  38%|████▌       | 567/1495 [03:33<05:44,  2.70it/s]
[Running Accuracy]: 0.8131,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 567:  38%|███▊      | 567/1495 [03:33<05:44,  2.70it/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 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': 'B.<|endoftext|>'} 

prompt A chat 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 very strong noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have very strong noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have very strong noise?\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]: 0.8131,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 567:  38%|███▊      | 568/1495 [03:34<05:29,  2.81it/s]
[Running Accuracy]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 568:  38%|████▌       | 568/1495 [03:34<05:29,  2.81it/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>Does this image have very strong 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>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([-31.0312], 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]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 568:  38%|████▌       | 569/1495 [03:34<05:17,  2.92it/s]
[Running Accuracy]: 0.8137,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 569:  38%|████▏      | 569/1495 [03:34<05:17,  2.92it/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>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 severe is the noise in this picture?
A. Severe
B. Mild
C. Moderate
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. Mild
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the noise in this picture?\nA. Severe\nB. Mild\nC. Moderate\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]: 0.8137,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 569:  38%|████▏      | 570/1495 [03:34<05:11,  2.97it/s]
[Running Accuracy]: 0.8140,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 570:  38%|███     | 570/1495 [03:34<05:11,  2.97it/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 severe is the noise in this picture?\nA. Severe\nB. Mild\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 object most affected by motion blur in the image?
A. Track
B. Person above
C. Lawn
D. Person below
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the object most affected by motion blur in the image?
A. Track
B. Person above
C. Lawn
D. Person below
Answer with the option's letter from the given choices directly.

prompts: [["What is the object most affected by motion blur in the image?\nA. Track\nB. Person above\nC. Lawn\nD. Person below\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]: 0.8140,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 570:  38%|███     | 571/1495 [03:35<05:12,  2.96it/s]
[Running Accuracy]: 0.8144,[Response]: D.<|endoftext|>, [Correct Ans]: Person below, , [Prog]: 571:  38%|▊ | 571/1495 [03:35<05:12,  2.96it/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>What is the object most affected by motion blur in the image?\nA. Track\nB. Person above\nC. Lawn\nD. Person below\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 trees contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the trees contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the trees contain rich texture?\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]: 0.8144,[Response]: D.<|endoftext|>, [Correct Ans]: Person below, , [Prog]: 571:  38%|▊ | 572/1495 [03:35<06:32,  2.35it/s]
[Running Accuracy]: 0.8147,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 572:  38%|████▏      | 572/1495 [03:35<06:32,  2.35it/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>Does the trees contain rich 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>Does the cat in this image look sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the cat in this image look sharp?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the cat in this image look sharp?\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])
 A.

[Running Accuracy]: 0.8147,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 572:  38%|████▏      | 573/1495 [03:36<05:58,  2.57it/s]
[Running Accuracy]: 0.8150,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 573:  38%|████▌       | 573/1495 [03:36<05:58,  2.57it/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>Does the cat in this image look 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>How is the overall 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 overall 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 overall sharpness of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], 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]: 0.8150,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 573:  38%|████▌       | 574/1495 [03:36<05:37,  2.73it/s]
[Running Accuracy]: 0.8153,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 574:  38%|███     | 574/1495 [03:36<05:37,  2.73it/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 overall sharpness 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 overall 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 is the overall clarity 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 clarity of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1406], 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]: 0.8153,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 574:  38%|███     | 575/1495 [03:36<05:26,  2.82it/s]
[Running Accuracy]: 0.8157,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 575:  38%|███     | 575/1495 [03:36<05:26,  2.82it/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 overall clarity 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 railing 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 railing 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 railing in the image?\nA. Average\nB. Good\nC. Poor\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]: 0.8157,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 575:  39%|███     | 576/1495 [03:37<05:14,  2.92it/s]
[Running Accuracy]: 0.8142,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 576:  39%|███▊      | 576/1495 [03:37<05:14,  2.92it/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 color saturation of the railing 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>What is the most apparent distortion in this image?
A. Under=exposure
B. Blur
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. Under=exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion in this image?\nA. Under=exposure\nB. Blur\nC. 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]: 0.8142,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 576:  39%|███▊      | 577/1495 [03:37<05:05,  3.00it/s]
[Running Accuracy]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 577:  39%|███▍     | 577/1495 [03:37<05:05,  3.00it/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>What is the most apparent distortion in this image?\nA. Under=exposure\nB. Blur\nC. 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>Which distortion is most apparent in this image?
A. Compression Artifacts
B. Noise
C. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion is most apparent in this image?
A. Compression Artifacts
B. Noise
C. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion is most apparent in this image?\nA. Compression Artifacts\nB. Noise\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]: 0.8146,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 577:  39%|███▍     | 578/1495 [03:37<05:25,  2.82it/s]
[Running Accuracy]: 0.8149,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 578:  39%|█▏ | 578/1495 [03:37<05:25,  2.82it/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>Which distortion is most apparent in this image?\nA. Compression Artifacts\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>What's the clearest object in this picture?
A. People
B. Track
C. Train
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What's the clearest object in this picture?
A. People
B. Track
C. Train
Answer with the option's letter from the given choices directly.

prompts: [["What's the clearest object in this picture?\nA. People\nB. Track\nC. Train\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]: 0.8149,[Response]: C.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 578:  39%|█▏ | 579/1495 [03:38<06:29,  2.35it/s]
[Running Accuracy]: 0.8135,[Response]: C.<|endoftext|>, [Correct Ans]: Track, , [Prog]: 579:  39%|███▍     | 579/1495 [03:38<06:29,  2.35it/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>What's the clearest object in this picture?\nA. People\nB. Track\nC. Train\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Pleasant
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. Pleasant
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. Pleasant\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]: 0.8135,[Response]: C.<|endoftext|>, [Correct Ans]: Track, , [Prog]: 579:  39%|███▍     | 580/1495 [03:38<05:59,  2.54it/s]
[Running Accuracy]: 0.8138,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 580:  39%|███▉      | 580/1495 [03:38<05:59,  2.54it/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>What kind of visual impression does the image give?\nA. Vibrant\nB. Dark\nC. Fresh\nD. Pleasant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Clear
B. Moderate
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Clear\nB. Moderate\nC. Blurry\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])
 A.

[Running Accuracy]: 0.8138,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 580:  39%|███▉      | 581/1495 [03:39<05:43,  2.66it/s]
[Running Accuracy]: 0.8141,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 581:  39%|███▍     | 581/1495 [03:39<05:43,  2.66it/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?\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>What is the worst distortion of the tree 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 of the tree 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 of the tree 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([-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]: 0.8141,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 581:  39%|███▌     | 582/1495 [03:39<05:33,  2.73it/s]
[Running Accuracy]: 0.8144,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 582:  39%|▊ | 582/1495 [03:39<05:33,  2.73it/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>What is the worst distortion of the tree 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': 'B.<|endoftext|>'} 

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

prompts: [["Is the puppy the focal point in this 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]: 0.8144,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 582:  39%|▊ | 583/1495 [03:39<05:29,  2.77it/s]
[Running Accuracy]: 0.8148,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 583:  39%|████▎      | 583/1495 [03:39<05:29,  2.77it/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>Is the puppy the focal point 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>To what degree is the seat in this image blurred?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what degree is the seat in this image blurred?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["To what degree is the seat in this image blurred?\nA. Moderate\nB. Severe\nC. Slight\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]: 0.8148,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 583:  39%|████▎      | 584/1495 [03:40<05:19,  2.86it/s]
[Running Accuracy]: 0.8151,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 584:  39%|███▏    | 584/1495 [03:40<05:19,  2.86it/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>To what degree is the seat in this image blurred?\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>What distortion occurs in this image?
A. Blur
B. Underexposure
C. Faded color
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion occurs in this image?
A. Blur
B. Underexposure
C. Faded color
Answer with the option's letter from the given choices directly.

prompts: [["What distortion occurs in this image?\nA. Blur\nB. Underexposure\nC. Faded color\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]: 0.8151,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 584:  39%|███▏    | 585/1495 [03:40<05:08,  2.95it/s]
[Running Accuracy]: 0.8154,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 585:  39%|███▉      | 585/1495 [03:40<05:08,  2.95it/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>What distortion occurs in this image?\nA. Blur\nB. Underexposure\nC. Faded color\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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([-30.9219], 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. No

[Running Accuracy]: 0.8154,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 585:  39%|███▉      | 586/1495 [03:40<05:09,  2.94it/s]
[Running Accuracy]: 0.8157,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 586:  39%|███▌     | 586/1495 [03:40<05:09,  2.94it/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>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': '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 lighting of the grass of this image?
A. Good
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the grass of this image?
A. Good
B. Medium
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the grass of this image?\nA. Good\nB. Medium\nC. Dark\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])
 A.

[Running Accuracy]: 0.8157,[Response]: A. No<|endoftext|>, [Correct Ans]: No, , [Prog]: 586:  39%|███▌     | 587/1495 [03:41<04:59,  3.03it/s]
[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 587:  39%|███▉      | 587/1495 [03:41<04:59,  3.03it/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 lighting of the grass of this image?\nA. Good\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>Which of the following image quality issues does this image not have?
A. Noise
B. Overexposure
C. Out of focus
D. Underexposure
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. Overexposure
C. Out of focus
D. Underexposure
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. Overexposure\nC. Out of focus\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])
 D.

[Running Accuracy]: 0.8160,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 587:  39%|███▉      | 588/1495 [03:41<04:56,  3.06it/s]
[Running Accuracy]: 0.8146,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 588:  39%|▊ | 588/1495 [03:41<04:56,  3.06it/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>Which of the following image quality issues does this image not have?\nA. Noise\nB. Overexposure\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>Is the main color of the airplane in the image blue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main color of the airplane in the image blue?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main color of the airplane in the image blue?\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]: 0.8146,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 588:  39%|▊ | 589/1495 [03:41<04:51,  3.11it/s]
[Running Accuracy]: 0.8132,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 589:  39%|████▎      | 589/1495 [03:41<04:51,  3.11it/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>Is the main color of the airplane in the image 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>Does the image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have motion blur?\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])
 A.

[Running Accuracy]: 0.8132,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 589:  39%|████▎      | 590/1495 [03:42<04:41,  3.22it/s]
[Running Accuracy]: 0.8136,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 590:  39%|████▎      | 590/1495 [03:42<04:41,  3.22it/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>Does the 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 it correct to say, both blurriness and overexposure occurs in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is it correct to say, both blurriness and overexposure occurs in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is it correct to say, both blurriness and overexposure occurs 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]: 0.8136,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 590:  40%|████▎      | 591/1495 [03:42<06:07,  2.46it/s]
[Running Accuracy]: 0.8139,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 591:  40%|████▎      | 591/1495 [03:42<06:07,  2.46it/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>Is it correct to say, both blurriness and overexposure occurs 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>Where does the light come from in this image?
A. from the side
B. from below
C. from behind
D. from above
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where does the light come from in this image?
A. from the side
B. from below
C. from behind
D. from above
Answer with the option's letter from the given choices directly.

prompts: [["Where does the light come from in this image?\nA. from the side\nB. from below\nC. from behind\nD. from above\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]: 0.8139,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 591:  40%|████▎      | 592/1495 [03:42<05:47,  2.60it/s]
[Running Accuracy]: 0.8125,[Response]: B.<|endoftext|>, [Correct Ans]: from above, , [Prog]: 592:  40%|█▌  | 592/1495 [03:42<05:47,  2.60it/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>Where does the light come from in this image?\nA. from the side\nB. from below\nC. from behind\nD. from above\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 the image?
A. Sun
B. Trees
C. Shoulder
D. Helmet
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of the image?
A. Sun
B. Trees
C. Shoulder
D. Helmet
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of the image?\nA. Sun\nB. Trees\nC. Shoulder\nD. Helmet\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]: 0.8125,[Response]: B.<|endoftext|>, [Correct Ans]: from above, , [Prog]: 592:  40%|█▌  | 593/1495 [03:43<05:26,  2.76it/s]
[Running Accuracy]: 0.8128,[Response]: D.<|endoftext|>, [Correct Ans]: Helmet, , [Prog]: 593:  40%|███▏    | 593/1495 [03:43<05:26,  2.76it/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>Where is the focus of the image?\nA. Sun\nB. Trees\nC. Shoulder\nD. Helmet\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 level of blurriness exists in the parked bicycle in this image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What level of blurriness exists in the parked bicycle in this image?
A. Moderate
B. Slight
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["What level of blurriness exists in the parked bicycle in this image?\nA. Moderate\nB. Slight\nC. Severe\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]: 0.8128,[Response]: D.<|endoftext|>, [Correct Ans]: Helmet, , [Prog]: 593:  40%|███▏    | 594/1495 [03:43<05:14,  2.86it/s]
[Running Accuracy]: 0.8131,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 594:  40%|███▏    | 594/1495 [03:43<05:14,  2.86it/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>What level of blurriness exists in the parked bicycle in this 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>Do the fruits havee a lot of noise in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the fruits havee a lot of noise in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the fruits havee a lot of noise in this 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]: 0.8131,[Response]: C.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 594:  40%|███▏    | 595/1495 [03:43<05:03,  2.96it/s]
[Running Accuracy]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 595:  40%|████▍      | 595/1495 [03:43<05:03,  2.96it/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>Do the fruits havee a lot of 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>Are the feathers of the bird in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the feathers of the bird in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the feathers of the bird in the image clear?\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]: 0.8134,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 595:  40%|████▍      | 596/1495 [03:44<04:55,  3.04it/s]
[Running Accuracy]: 0.8121,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 596:  40%|████▊       | 596/1495 [03:44<04:55,  3.04it/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>Are the feathers of the bird 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>Is the dog 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 dog very clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog very clear in this image?\nA. Yes\nB. No\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]: 0.8121,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 596:  40%|████▊       | 597/1495 [03:44<04:48,  3.11it/s]
[Running Accuracy]: 0.8124,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 597:  40%|████▊       | 597/1495 [03:44<04:48,  3.11it/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>Is the dog 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>How bright is 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 this picture?
A. Bright
B. Dim
C. Normal
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Dim\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]: 0.8124,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 597:  40%|████▊       | 598/1495 [03:44<05:14,  2.86it/s]
[Running Accuracy]: 0.8127,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 598:  40%|████▍      | 598/1495 [03:44<05:14,  2.86it/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 bright is 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 there any defocus 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 defocus problem in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any defocus problem 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])
 B.

[Running Accuracy]: 0.8127,[Response]: B.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 598:  40%|████▍      | 599/1495 [03:45<05:07,  2.91it/s]
[Running Accuracy]: 0.8130,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 599:  40%|████▊       | 599/1495 [03:45<05:07,  2.91it/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>Is there any defocus 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>How's the level of blur in the image?
A. Very blurry
B. Some blur
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the level of blur in the image?
A. Very blurry
B. Some blur
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How's the level of blur in the image?\nA. Very blurry\nB. Some blur\nC. Not blurry at all\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]: 0.8130,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 599:  40%|████▊       | 600/1495 [03:45<05:01,  2.97it/s]
[Running Accuracy]: 0.8117,[Response]: C.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 600:  40%|██   | 600/1495 [03:45<05:01,  2.97it/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's the level of blur in the image?\nA. Very blurry\nB. Some blur\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat 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 fruits clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the fruits clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the fruits clear in this image?\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]: 0.8117,[Response]: C.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 600:  40%|██   | 601/1495 [03:45<04:58,  2.99it/s]
[Running Accuracy]: 0.8120,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 601:  40%|████▊       | 601/1495 [03:45<04:58,  2.99it/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>Are the fruits 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 this found photo medication bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of this found photo medication bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of this found photo medication bright?\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]: 0.8120,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 601:  40%|████▊       | 602/1495 [03:46<04:53,  3.04it/s]
[Running Accuracy]: 0.8123,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 602:  40%|████▍      | 602/1495 [03:46<04:53,  3.04it/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>Is the color of this found photo medication 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 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([-31.0312], 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]: 0.8123,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 602:  40%|████▍      | 603/1495 [03:46<04:46,  3.11it/s]
[Running Accuracy]: 0.8109,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 603:  40%|███▏    | 603/1495 [03:46<04:46,  3.11it/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 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 overall quality of this image?
A. Bad
B. Good
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall quality of this image?
A. Bad
B. Good
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall quality of this image?\nA. Bad\nB. Good\nC. Acceptable\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]: 0.8109,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 603:  40%|███▏    | 604/1495 [03:47<06:06,  2.43it/s]
[Running Accuracy]: 0.8113,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 604:  40%|█▌  | 604/1495 [03:47<06:06,  2.43it/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 overall quality of this image?\nA. Bad\nB. Good\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>Is the color of the fire safety equipment signs 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 fire safety equipment signs 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 fire safety equipment signs in this image bright?\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]: 0.8113,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 604:  40%|█▌  | 605/1495 [03:47<05:45,  2.57it/s]
[Running Accuracy]: 0.8099,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 605:  40%|████▍      | 605/1495 [03:47<05:45,  2.57it/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>Is the color of the fire safety equipment signs 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>How is the composition of this picture?
A. Fair
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this picture?
A. Fair
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this picture?\nA. Fair\nB. Poor\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.2812], 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]: 0.8099,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 605:  41%|████▍      | 606/1495 [03:47<05:28,  2.70it/s]
[Running Accuracy]: 0.8086,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 606:  41%|████      | 606/1495 [03:47<05:28,  2.70it/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 composition of this picture?\nA. Fair\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>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([-31.0156], 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]: 0.8086,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 606:  41%|████      | 607/1495 [03:48<05:14,  2.83it/s]
[Running Accuracy]: 0.8072,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 607:  41%|███▋     | 607/1495 [03:48<05:14,  2.83it/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 clear is this picture?\nA. Normal\nB. Blurry\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>Does the figurine in the image look symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the figurine in the image look symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the figurine in the image look symmetrical?\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]: 0.8072,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 607:  41%|███▋     | 608/1495 [03:48<05:03,  2.92it/s]
[Running Accuracy]: 0.8059,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 608:  41%|████▍      | 608/1495 [03:48<05:03,  2.92it/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>Does the figurine in the image look 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>How clear are the elephants in this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the elephants in this picture?
A. Clear
B. Normal
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the elephants in this picture?\nA. Clear\nB. Normal\nC. Blurry\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]: 0.8059,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 608:  41%|████▍      | 609/1495 [03:48<04:57,  2.97it/s]
[Running Accuracy]: 0.8062,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 609:  41%|███▎    | 609/1495 [03:48<04:57,  2.97it/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 clear are the elephants in 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>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([-30.9531], 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]: 0.8062,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 609:  41%|███▎    | 610/1495 [03:49<04:49,  3.06it/s]
[Running Accuracy]: 0.8066,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 610:  41%|████▍      | 610/1495 [03:49<04:49,  3.06it/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>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 would you rate the 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 would you rate the clarity of 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 this image?\nA. High\nB. Acceptable\nC. Low\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]: 0.8066,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 610:  41%|████▍      | 611/1495 [03:49<04:47,  3.08it/s]
[Running Accuracy]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 611:  41%|█▋  | 611/1495 [03:49<04:47,  3.08it/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 would you rate the clarity of this image?\nA. High\nB. Acceptable\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>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([-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]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 611:  41%|█▋  | 612/1495 [03:49<04:47,  3.07it/s]
[Running Accuracy]: 0.8056,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 612:  41%|████▌      | 612/1495 [03:49<04:47,  3.07it/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>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>What objects are in the center of this picture?
A. Trees
B. Two women
C. Shops
D. Two men
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What objects are in the center of this picture?
A. Trees
B. Two women
C. Shops
D. Two men
Answer with the option's letter from the given choices directly.

prompts: [["What objects are in the center of this picture?\nA. Trees\nB. Two women\nC. Shops\nD. Two men\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]: 0.8056,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 612:  41%|████▌      | 613/1495 [03:50<06:07,  2.40it/s]
[Running Accuracy]: 0.8059,[Response]: B.<|endoftext|>, [Correct Ans]: Two women, , [Prog]: 613:  41%|██   | 613/1495 [03:50<06:07,  2.40it/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>What objects are in the center of this picture?\nA. Trees\nB. Two women\nC. Shops\nD. Two men\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 pitcure 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 pitcure 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 pitcure clearer than the surrounding areas?\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]: 0.8059,[Response]: B.<|endoftext|>, [Correct Ans]: Two women, , [Prog]: 613:  41%|██   | 614/1495 [03:50<05:42,  2.57it/s]
[Running Accuracy]: 0.8046,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 614:  41%|████▌      | 614/1495 [03:50<05:42,  2.57it/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>Is the center of this pitcure 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>Is this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture in focus?\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])
 A.

[Running Accuracy]: 0.8046,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 614:  41%|████▌      | 615/1495 [03:51<05:22,  2.73it/s]
[Running Accuracy]: 0.8049,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 615:  41%|████▉       | 615/1495 [03:51<05:22,  2.73it/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>Is this picture 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 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([-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]: 0.8049,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 615:  41%|████▉       | 616/1495 [03:51<05:11,  2.83it/s]
[Running Accuracy]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 616:  41%|████▉       | 616/1495 [03:51<05:11,  2.83it/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>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>How bright is the sky in 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 the sky in this picture?
A. Normal
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the sky in this picture?\nA. Normal\nB. Bright\nC. Dark\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])
 B.

[Running Accuracy]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 616:  41%|████▉       | 617/1495 [03:51<04:58,  2.95it/s]
[Running Accuracy]: 0.8039,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 617:  41%|████▏     | 617/1495 [03:51<04:58,  2.95it/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 bright is the sky in 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>How would you rate the noise level of this image?
A. Srong
B. Acceptable
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the noise level of this image?
A. Srong
B. Acceptable
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the noise level of this image?\nA. Srong\nB. Acceptable\nC. Weak\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]: 0.8039,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 617:  41%|████▏     | 618/1495 [03:51<04:51,  3.01it/s]
[Running Accuracy]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 618:  41%|███▋     | 618/1495 [03:51<04:51,  3.01it/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 would you rate the noise level of this image?\nA. Srong\nB. Acceptable\nC. Weak\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a dark feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark feeling?\nA. No\nB. Yes\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])
 B.

[Running Accuracy]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 618:  41%|███▋     | 619/1495 [03:52<04:51,  3.01it/s]
[Running Accuracy]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 619:  41%|████▌      | 619/1495 [03:52<04:51,  3.01it/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>Does this image give a dark 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>How is the color saturation 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 color saturation of 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 image?\nA. Good\nB. Fair\nC. Poor\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]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 619:  41%|████▌      | 620/1495 [03:52<04:46,  3.06it/s]
[Running Accuracy]: 0.8048,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 620:  41%|████▏     | 620/1495 [03:52<04:46,  3.06it/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 color saturation of 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 there any noise in the background of 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 the background of this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise in the background of this 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]: 0.8048,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 620:  42%|████▏     | 621/1495 [03:53<05:41,  2.56it/s]
[Running Accuracy]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 621:  42%|████▌      | 621/1495 [03:53<05:41,  2.56it/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>Is there any noise in the background 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>What kind of visual perception does the image give?
A. Fresh
B. Dark
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. Fresh
B. Dark
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. Fresh\nB. Dark\nC. Bright\nD. Happy\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]: 0.8052,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 621:  42%|████▌      | 622/1495 [03:53<05:24,  2.69it/s]
[Running Accuracy]: 0.8055,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 622:  42%|████▏     | 622/1495 [03:53<05:24,  2.69it/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>What kind of visual perception does the image give?\nA. Fresh\nB. Dark\nC. Bright\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>How would you rate the clarity of the stores in the background?
A. Acceptable
B. Poor
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the stores in the background?
A. Acceptable
B. Poor
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the stores in the background?\nA. Acceptable\nB. Poor\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]: 0.8055,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 622:  42%|████▏     | 623/1495 [03:54<06:26,  2.26it/s]
[Running Accuracy]: 0.8042,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 623:  42%|████▏     | 623/1495 [03:54<06:26,  2.26it/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 would you rate the clarity of the stores in the background?\nA. Acceptable\nB. 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 lighting of the ferris wheel 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 ferris wheel 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 ferris wheel in this image?\nA. Dark\nB. Bright\nC. Medium\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]: 0.8042,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 623:  42%|████▏     | 624/1495 [03:54<06:39,  2.18it/s]
[Running Accuracy]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 624:  42%|███▎    | 624/1495 [03:54<06:39,  2.18it/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 lighting of the ferris wheel in 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>How would you rate the noise level of this image?
A. Srong
B. Weak
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the noise level of this image?
A. Srong
B. Weak
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the noise level of this image?\nA. Srong\nB. Weak\nC. Acceptable\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]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 624:  42%|███▎    | 625/1495 [03:54<06:02,  2.40it/s]
[Running Accuracy]: 0.8048,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 625:  42%|███▊     | 625/1495 [03:54<06:02,  2.40it/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 would you rate the noise level of this image?\nA. Srong\nB. Weak\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>What is the most severely overexposed object in the image?
A. Wooden sign
B. Ground
C. Flame
D. Ash
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severely overexposed object in the image?
A. Wooden sign
B. Ground
C. Flame
D. Ash
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severely overexposed object in the image?\nA. Wooden sign\nB. Ground\nC. Flame\nD. Ash\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]: 0.8048,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 625:  42%|███▊     | 626/1495 [03:55<05:42,  2.54it/s]
[Running Accuracy]: 0.8051,[Response]: C.<|endoftext|>, [Correct Ans]: Flame, , [Prog]: 626:  42%|███▊     | 626/1495 [03:55<05:42,  2.54it/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>What is the most severely overexposed object in the image?\nA. Wooden sign\nB. Ground\nC. Flame\nD. Ash\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Noise
C. Out of focus
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. Noise
C. Out of focus
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. Noise\nC. Out of focus\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]: 0.8051,[Response]: C.<|endoftext|>, [Correct Ans]: Flame, , [Prog]: 626:  42%|███▊     | 627/1495 [03:55<05:21,  2.70it/s]
[Running Accuracy]: 0.8038,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 627:  42%|▊ | 627/1495 [03:55<05:21,  2.70it/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>Which of the following image quality issues does not exist in this picture?\nA. Overexposure\nB. Noise\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>Is the little boy wearing a blue hat in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little boy wearing a blue hat in the picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the little boy wearing a blue hat in the picture clear?\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]: 0.8038,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 627:  42%|▊ | 628/1495 [03:55<05:10,  2.79it/s]
[Running Accuracy]: 0.8041,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 628:  42%|████▌      | 628/1495 [03:55<05:10,  2.79it/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>Is the little boy wearing a blue hat 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 is the main color tone of the vehicle in the image?
A. Green
B. Yellow
C. Blue
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color tone of the vehicle in the image?
A. Green
B. Yellow
C. Blue
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color tone of the vehicle in the image?\nA. Green\nB. Yellow\nC. Blue\nD. Red\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]: 0.8041,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 628:  42%|████▋      | 629/1495 [03:56<05:07,  2.81it/s]
[Running Accuracy]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 629:  42%|███▎    | 629/1495 [03:56<05:07,  2.81it/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>What is the main color tone of the vehicle in the image?\nA. Green\nB. Yellow\nC. Blue\nD. 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>Does this image give a dark 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 dark visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark visual impression?\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]: 0.8045,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 629:  42%|███▎    | 630/1495 [03:56<05:06,  2.82it/s]
[Running Accuracy]: 0.8048,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 630:  42%|████▋      | 630/1495 [03:56<05:06,  2.82it/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>Does this image give a dark 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 severe is the underexposure in this image?
A. Very severe underexposure
B. No underexposure
C. Moderate underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the underexposure in this image?
A. Very severe underexposure
B. No underexposure
C. Moderate underexposure
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the underexposure in this image?\nA. Very severe underexposure\nB. No underexposure\nC. Moderate 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])
 A.

[Running Accuracy]: 0.8048,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 630:  42%|████▋      | 631/1495 [03:57<05:59,  2.41it/s]
[Running Accuracy]: 0.8051,[Response]: A.<|endoftext|>, [Correct Ans]: Very severe underexposure, , [Prog]: 631:  42%|▍| 631/1495 [03:57<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>How severe is the underexposure in this image?\nA. Very severe underexposure\nB. No underexposure\nC. Moderate 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>Which object in the image is severely affected by motion blur?
A. The man in the back
B. The trees
C. The ground
D. The three men in the front
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. The man in the back
B. The trees
C. The ground
D. The three men in the front
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is severely affected by motion blur?\nA. The man in the back\nB. The trees\nC. The ground\nD. The three men in the front\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]: 0.8051,[Response]: A.<|endoftext|>, [Correct Ans]: Very severe underexposure, , [Prog]: 631:  42%|▍| 632/1495 [03:57<05:43
[Running Accuracy]: 0.8054,[Response]: D.<|endoftext|>, [Correct Ans]: The three men in the front, , [Prog]: 632:  42%|▍| 632/1495 [03:57<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>Which object in the image is severely affected by motion blur?\nA. The man in the back\nB. The trees\nC. The ground\nD. The three men in the front\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 dishes 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
Are the dishes emphasized in the center of this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the dishes 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([-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]: 0.8054,[Response]: D.<|endoftext|>, [Correct Ans]: The three men in the front, , [Prog]: 632:  42%|▍| 633/1495 [03:57<05:2
[Running Accuracy]: 0.8057,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 633:  42%|████▋      | 633/1495 [03:57<05:27,  2.63it/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>Are the dishes 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>How is the image clarity?
A. Blurry
B. Sharp
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Blurry
B. Sharp
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Blurry\nB. Sharp\nC. Moderate\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]: 0.8057,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 633:  42%|████▋      | 634/1495 [03:58<05:14,  2.74it/s]
[Running Accuracy]: 0.8044,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 634:  42%|███▍    | 634/1495 [03:58<05:14,  2.74it/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?\nA. Blurry\nB. Sharp\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>What is the darkest part in this image?
A. Wall
B. Window
C. Floor
D. Shelf
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the darkest part in this image?
A. Wall
B. Window
C. Floor
D. Shelf
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest part in this image?\nA. Wall\nB. Window\nC. Floor\nD. Shelf\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]: 0.8044,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 634:  42%|███▍    | 635/1495 [03:58<05:13,  2.74it/s]
[Running Accuracy]: 0.8047,[Response]: B.<|endoftext|>, [Correct Ans]: Window, , [Prog]: 635:  42%|███▍    | 635/1495 [03:58<05:13,  2.74it/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>What is the darkest part in this image?\nA. Wall\nB. Window\nC. Floor\nD. Shelf\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. 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 image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is 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([-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]: 0.8047,[Response]: B.<|endoftext|>, [Correct Ans]: Window, , [Prog]: 635:  43%|███▍    | 636/1495 [03:58<05:06,  2.80it/s]
[Running Accuracy]: 0.8050,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 636:  43%|████▋      | 636/1495 [03:58<05:06,  2.80it/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 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>Has the man's face been captured clearly?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Has the man's face been captured clearly?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Has the man's face been captured clearly?\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]: 0.8050,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 636:  43%|████▋      | 637/1495 [03:59<04:58,  2.87it/s]
[Running Accuracy]: 0.8053,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 637:  43%|████▋      | 637/1495 [03:59<04:58,  2.87it/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>Has the man's face been captured clearly?\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 red leaf 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 clarity of the red leaf in this image
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the red leaf in this image\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.7031], 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]: 0.8053,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 637:  43%|████▋      | 638/1495 [03:59<05:53,  2.42it/s]
[Running Accuracy]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 638:  43%|████▋      | 638/1495 [03:59<05:53,  2.42it/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 clarity of the red leaf in 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 is emphasized in the center of this image?
A. deck
B. street lamp
C. ship
D. trash can
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. deck
B. street lamp
C. ship
D. trash can
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. deck\nB. street lamp\nC. ship\nD. trash can\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]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 638:  43%|████▋      | 639/1495 [04:00<05:40,  2.51it/s]
[Running Accuracy]: 0.8059,[Response]: C.<|endoftext|>, [Correct Ans]: ship, , [Prog]: 639:  43%|████▎     | 639/1495 [04:00<05:40,  2.51it/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>Which object is emphasized in the center of this image?\nA. deck\nB. street lamp\nC. ship\nD. trash can\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 there in the image?
A. Backlighting
B. Overexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems are there in the image?
A. Backlighting
B. Overexposure
C. Motion blur
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems are there in the image?\nA. Backlighting\nB. Overexposure\nC. Motion blur\nD. Compression artifacts\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]: 0.8059,[Response]: C.<|endoftext|>, [Correct Ans]: ship, , [Prog]: 639:  43%|████▎     | 640/1495 [04:00<05:23,  2.64it/s]
[Running Accuracy]: 0.8047,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 640:  43%|█▎ | 640/1495 [04:00<05:23,  2.64it/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>What problems are there in the image?\nA. Backlighting\nB. Overexposure\nC. Motion blur\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>Does the image suffer from twisted blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image suffer from twisted blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image suffer from twisted blur?\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]: 0.8047,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 640:  43%|█▎ | 641/1495 [04:00<06:00,  2.37it/s]
[Running Accuracy]: 0.8050,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 641:  43%|████▋      | 641/1495 [04:00<06:00,  2.37it/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>Does the image suffer from twisted 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>What kind of distortion is visible in this image?
A. Noise
B. Motion Blur
C. Out of Focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion is visible in this image?
A. Noise
B. Motion Blur
C. Out of Focus
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion is visible in this image?\nA. Noise\nB. Motion Blur\nC. Out of Focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], 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]: 0.8050,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 641:  43%|████▋      | 642/1495 [04:01<05:27,  2.60it/s]
[Running Accuracy]: 0.8053,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 642:  43%|███▊     | 642/1495 [04:01<05:27,  2.60it/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>What kind of distortion is visible in this image?\nA. Noise\nB. Motion Blur\nC. 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 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([-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]: 0.8053,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 642:  43%|███▊     | 643/1495 [04:01<05:13,  2.72it/s]
[Running Accuracy]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 643:  43%|████▎     | 643/1495 [04:01<05:13,  2.72it/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 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 severe is the motion blur in this picture?
A. Moderate
B. Severe
C. Mild
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the motion blur in this picture?
A. Moderate
B. Severe
C. Mild
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the motion blur in this picture?\nA. Moderate\nB. Severe\nC. Mild\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]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 643:  43%|████▎     | 644/1495 [04:02<06:05,  2.33it/s]
[Running Accuracy]: 0.8059,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 644:  43%|███▍    | 644/1495 [04:02<06:05,  2.33it/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 severe is the motion blur in this picture?\nA. Moderate\nB. Severe\nC. Mild\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.0312], 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]: 0.8059,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 644:  43%|███▍    | 645/1495 [04:02<06:05,  2.33it/s]
[Running Accuracy]: 0.8062,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 645:  43%|█████▏      | 645/1495 [04:02<06:05,  2.33it/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>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 the buildings?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the buildings?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the buildings?\nA. Low\nB. High\nC. Acceptable\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]: 0.8062,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 645:  43%|█████▏      | 646/1495 [04:03<06:47,  2.08it/s]
[Running Accuracy]: 0.8050,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 646:  43%|█▋  | 646/1495 [04:03<06:47,  2.08it/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 clarity of the buildings?\nA. Low\nB. High\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 distortion happens in the image?
A. Underexposure
B. Snow
C. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion happens in the image?
A. Underexposure
B. Snow
C. Blur
Answer with the option's letter from the given choices directly.

prompts: [["What distortion happens in the image?\nA. Underexposure\nB. Snow\nC. 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])
 B.

[Running Accuracy]: 0.8050,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 646:  43%|█▋  | 647/1495 [04:03<06:04,  2.33it/s]
[Running Accuracy]: 0.8053,[Response]: B.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 647:  43%|████▎     | 647/1495 [04:03<06:04,  2.33it/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>What distortion happens in the image?\nA. Underexposure\nB. Snow\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 main subject well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject well-defined?\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]: 0.8053,[Response]: B.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 647:  43%|████▎     | 648/1495 [04:03<05:40,  2.49it/s]
[Running Accuracy]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 648:  43%|████▊      | 648/1495 [04:03<05:40,  2.49it/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>Is the main subject well-defined?\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 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([-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]: 0.8056,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 648:  43%|████▊      | 649/1495 [04:04<05:16,  2.67it/s]
[Running Accuracy]: 0.8043,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 649:  43%|█████▏      | 649/1495 [04:04<05:16,  2.67it/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>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>Is the camera content distinguishable?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the camera content distinguishable?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the camera content distinguishable?\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]: 0.8043,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 649:  43%|█████▏      | 650/1495 [04:04<05:03,  2.78it/s]
[Running Accuracy]: 0.8046,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 650:  43%|████▊      | 650/1495 [04:04<05:03,  2.78it/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>Is the camera content distinguishable?\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 issues does not exist 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
Which of the following image quality issues does not exist 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: [["Which of the following image quality issues does not exist 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([-31.2656], 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]: 0.8046,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 650:  44%|████▊      | 651/1495 [04:04<04:55,  2.85it/s]
[Running Accuracy]: 0.8049,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 651:  44%|▍| 651/1495 [04:04<04:55,  2.85it/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>Which of the following image quality issues does not exist 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': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 red flowers in the middle of 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 red flowers in the middle of 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 red flowers in the middle of this image?\nA. Medium\nB. Vibrant\nC. Monotonous\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]: 0.8049,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 651:  44%|▍| 652/1495 [04:05<04:47,  2.93it/s]
[Running Accuracy]: 0.8052,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 652:  44%|███    | 652/1495 [04:05<04:47,  2.93it/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 color of the red flowers in the middle of 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>Is there any noise issue 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 issue in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any noise issue 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]: 0.8052,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 652:  44%|███    | 653/1495 [04:05<04:43,  2.97it/s]
[Running Accuracy]: 0.8055,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 653:  44%|█████▏      | 653/1495 [04:05<04:43,  2.97it/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>Is there any noise 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>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([-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]: 0.8055,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 653:  44%|█████▏      | 654/1495 [04:05<04:34,  3.07it/s]
[Running Accuracy]: 0.8058,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 654:  44%|███▍    | 654/1495 [04:05<04:34,  3.07it/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 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>What is the color saturation of the withered tree in the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color saturation of the withered tree in the image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["What is the color saturation of the withered tree in the image?\nA. High\nB. Medium\nC. Low\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]: 0.8058,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 654:  44%|███▌    | 655/1495 [04:06<04:33,  3.07it/s]
[Running Accuracy]: 0.8061,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 655:  44%|████▊      | 655/1495 [04:06<04:33,  3.07it/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>What is the color saturation of the withered tree in 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>How is the color saturation of the flowers 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 flowers 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 flowers in the image?\nA. Good\nB. Average\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]: 0.8061,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 655:  44%|████▊      | 656/1495 [04:06<04:30,  3.10it/s]
[Running Accuracy]: 0.8064,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 656:  44%|████▍     | 656/1495 [04:06<04:30,  3.10it/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 color saturation of the flowers 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>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([-31.0312], 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]: 0.8064,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 656:  44%|████▍     | 657/1495 [04:06<04:29,  3.11it/s]
[Running Accuracy]: 0.8067,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 657:  44%|█████▎      | 657/1495 [04:06<04:29,  3.11it/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>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 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([-31.3750], 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]: 0.8067,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 657:  44%|█████▎      | 658/1495 [04:07<04:31,  3.09it/s]
[Running Accuracy]: 0.8055,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 658:  44%|████▊      | 658/1495 [04:07<04:31,  3.09it/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>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 object in this image is the focus?
A. The sky
B. The man with the bow
C. The yellow castle
D. The blue castle
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. The sky
B. The man with the bow
C. The yellow castle
D. The blue castle
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. The sky\nB. The man with the bow\nC. The yellow castle\nD. The blue castle\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]: 0.8055,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 658:  44%|████▊      | 659/1495 [04:07<05:17,  2.63it/s]
[Running Accuracy]: 0.8058,[Response]: B.<|endoftext|>, [Correct Ans]: The man with the bow, , [Prog]: 659:  44%|▍| 659/1495 [04:07<05:17,  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 this image is the focus?\nA. The sky\nB. The man with the bow\nC. The yellow castle\nD. The blue castle\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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([-31.4219], 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]: 0.8058,[Response]: B.<|endoftext|>, [Correct Ans]: The man with the bow, , [Prog]: 659:  44%|▍| 660/1495 [04:07<05:08,  2.
[Running Accuracy]: 0.8061,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 660:  44%|████▍     | 660/1495 [04:07<05:08,  2.70it/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 clarity 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 the image shot in a dimly-lit condition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image shot in a dimly-lit condition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image shot in a dimly-lit condition?\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]: 0.8061,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 660:  44%|████▍     | 661/1495 [04:08<04:55,  2.82it/s]
[Running Accuracy]: 0.8064,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 661:  44%|████▊      | 661/1495 [04:08<04:55,  2.82it/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>Is the image shot in a dimly-lit condition?\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. Overexposure
B. Noise
C. Underexposure
D. OutOfFocus
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. Overexposure
B. Noise
C. Underexposure
D. OutOfFocus
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. Overexposure\nB. Noise\nC. Underexposure\nD. OutOfFocus\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]: 0.8064,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 661:  44%|████▊      | 662/1495 [04:08<04:48,  2.89it/s]
[Running Accuracy]: 0.8051,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 662:  44%|▉ | 662/1495 [04:08<04:48,  2.89it/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>Which of the following quality issues does not exist in this image?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. OutOfFocus\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["What makes the background of the image less visible?\nA. Underexposure\nB. Blur\nC. 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])
 C.

[Running Accuracy]: 0.8051,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 662:  44%|▉ | 663/1495 [04:09<05:15,  2.64it/s]
[Running Accuracy]: 0.8054,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 663:  44%|▉ | 663/1495 [04:09<05:15,  2.64it/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>What makes the background of the image less visible?\nA. Underexposure\nB. Blur\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>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])
 A.

[Running Accuracy]: 0.8054,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 663:  44%|▉ | 664/1495 [04:09<04:58,  2.78it/s]
[Running Accuracy]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 664:  44%|█████▎      | 664/1495 [04:09<04:58,  2.78it/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>Does this picture 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>Are the shadow and light well-balanced in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the shadow and light well-balanced in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the shadow and light well-balanced in this image?\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]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 664:  44%|█████▎      | 665/1495 [04:09<04:49,  2.87it/s]
[Running Accuracy]: 0.8030,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 665:  44%|████▉      | 665/1495 [04:09<04:49,  2.87it/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>Are the shadow and light well-balanced 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 there too much noise in the overall image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there too much noise in the overall image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there too much noise in the overall 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]: 0.8030,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 665:  45%|████▉      | 666/1495 [04:09<04:46,  2.90it/s]
[Running Accuracy]: 0.8033,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 666:  45%|█████▎      | 666/1495 [04:09<04:46,  2.90it/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>Is there too much noise in the overall 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 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([-31.0156], 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]: 0.8033,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 666:  45%|█████▎      | 667/1495 [04:10<04:55,  2.81it/s]
[Running Accuracy]: 0.8036,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 667:  45%|███▌    | 667/1495 [04:10<04:55,  2.81it/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 quality of this picture?\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>Are the buildings in this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the buildings in this picture colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the buildings in this picture colorful?\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]: 0.8036,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 667:  45%|███▌    | 668/1495 [04:10<05:49,  2.37it/s]
[Running Accuracy]: 0.8039,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 668:  45%|█████▎      | 668/1495 [04:10<05:49,  2.37it/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>Are the buildings in 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>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([-30.5781], 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]: 0.8039,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 668:  45%|█████▎      | 669/1495 [04:11<05:24,  2.55it/s]
[Running Accuracy]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 669:  45%|████▉      | 669/1495 [04:11<05:24,  2.55it/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>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 the pedestrian in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pedestrian in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the pedestrian in this image clear?\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]: 0.8042,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 669:  45%|████▉      | 670/1495 [04:11<05:11,  2.65it/s]
[Running Accuracy]: 0.8045,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 670:  45%|█████▍      | 670/1495 [04:11<05:11,  2.65it/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>Is the pedestrian 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>What is the sharpest part in this image?
A. Crow
B. Sky
C. Ground
D. Mountain
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest part in this image?
A. Crow
B. Sky
C. Ground
D. Mountain
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest part in this image?\nA. Crow\nB. Sky\nC. Ground\nD. Mountain\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]: 0.8045,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 670:  45%|█████▍      | 671/1495 [04:12<05:41,  2.41it/s]
[Running Accuracy]: 0.8033,[Response]: C.<|endoftext|>, [Correct Ans]: Crow, , [Prog]: 671:  45%|████▍     | 671/1495 [04:12<05:41,  2.41it/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>What is the sharpest part in this image?\nA. Crow\nB. Sky\nC. Ground\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>Is the most prominent color in the image orange?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the most prominent color in the image orange?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the most prominent color in the image orange?\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]: 0.8033,[Response]: C.<|endoftext|>, [Correct Ans]: Crow, , [Prog]: 671:  45%|████▍     | 672/1495 [04:12<05:19,  2.58it/s]
[Running Accuracy]: 0.8036,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 672:  45%|████▉      | 672/1495 [04:12<05:19,  2.58it/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>Is the most prominent color in the image orange?\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. 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([-30.4375], 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]: 0.8036,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 672:  45%|████▉      | 673/1495 [04:13<06:04,  2.25it/s]
[Running Accuracy]: 0.8039,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 673:  45%|█████▍      | 673/1495 [04:13<06:04,  2.25it/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>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 most serious quality issue in the image?
A. Compression distortion
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. Compression distortion
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. Compression distortion\nB. Overexposure\nC. Motion blur\nD. Noise\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])
 D.

[Running Accuracy]: 0.8039,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 673:  45%|█████▍      | 674/1495 [04:13<05:37,  2.44it/s]
[Running Accuracy]: 0.8042,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 674:  45%|████     | 674/1495 [04:13<05:37,  2.44it/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>What is the most serious quality issue in the image?\nA. Compression distortion\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>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([-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])
 A.

[Running Accuracy]: 0.8042,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 674:  45%|████     | 675/1495 [04:13<05:11,  2.63it/s]
[Running Accuracy]: 0.8044,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 675:  45%|█████▍      | 675/1495 [04:13<05:11,  2.63it/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>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>Rate the clarity of the image.
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Rate the clarity of the image.
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["Rate the clarity 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]: 0.8044,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 675:  45%|█████▍      | 676/1495 [04:13<04:53,  2.79it/s]
[Running Accuracy]: 0.8047,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 676:  45%|████▌     | 676/1495 [04:13<04:53,  2.79it/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>Rate the clarity 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>What is emphasized in the center of this picture?
A. Dog
B. Monitor
C. Chair
D. Table
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is emphasized in the center of this picture?
A. Dog
B. Monitor
C. Chair
D. Table
Answer with the option's letter from the given choices directly.

prompts: [["What is emphasized in the center of this picture?\nA. Dog\nB. Monitor\nC. Chair\nD. Table\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]: 0.8047,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 676:  45%|████▌     | 677/1495 [04:14<04:53,  2.79it/s]
[Running Accuracy]: 0.8050,[Response]: A.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 677:  45%|████▉      | 677/1495 [04:14<04:53,  2.79it/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>What is emphasized in the center of this picture?\nA. Dog\nB. Monitor\nC. Chair\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>What is the brightest color in this image?
A. Black
B. Green
C. Blue
D. Purple
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. Black
B. Green
C. Blue
D. Purple
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. Black\nB. Green\nC. Blue\nD. Purple\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]: 0.8050,[Response]: A.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 677:  45%|████▉      | 678/1495 [04:14<04:49,  2.82it/s]
[Running Accuracy]: 0.8053,[Response]: C.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 678:  45%|████▌     | 678/1495 [04:14<04:49,  2.82it/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>What is the brightest color in this image?\nA. Black\nB. Green\nC. Blue\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>How's the focus in this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus in this image?
A. Good
B. Acceptable
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus in this image?\nA. Good\nB. Acceptable\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]: 0.8053,[Response]: C.<|endoftext|>, [Correct Ans]: Blue, , [Prog]: 678:  45%|████▌     | 679/1495 [04:15<04:50,  2.81it/s]
[Running Accuracy]: 0.8041,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 679:  45%|█▊  | 679/1495 [04:15<04:50,  2.81it/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's the focus in 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>How would you rate the lighting of this image?
A. Bright
B. Dark
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. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of this image?\nA. Bright\nB. Dark\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]: 0.8041,[Response]: C.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 679:  45%|█▊  | 680/1495 [04:15<04:55,  2.76it/s]
[Running Accuracy]: 0.8029,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 680:  45%|████▌     | 680/1495 [04:15<04:55,  2.76it/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 would you rate the lighting of this image?\nA. Bright\nB. 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>What is the major distortion in this image?
A. Noise
B. Underexposure
C. Motion 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. Underexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the major distortion in this image?\nA. Noise\nB. Underexposure\nC. Motion Blur\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])
 A.

[Running Accuracy]: 0.8029,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 680:  46%|████▌     | 681/1495 [04:15<04:45,  2.85it/s]
[Running Accuracy]: 0.8032,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 681:  46%|████     | 681/1495 [04:15<04:45,  2.85it/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>What is the major distortion in this image?\nA. Noise\nB. Underexposure\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>What distortion is not in this picture?
A. Underexposure
B. Noise
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion is not in this picture?
A. Underexposure
B. Noise
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion is not in this picture?\nA. Underexposure\nB. Noise\nC. Motion blur\nD. Overexposure\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])
 A.

[Running Accuracy]: 0.8032,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 681:  46%|████     | 682/1495 [04:16<04:42,  2.88it/s]
[Running Accuracy]: 0.8021,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 682:  46%|█▎ | 682/1495 [04:16<04:42,  2.88it/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>What distortion is not in this picture?\nA. Underexposure\nB. Noise\nC. Motion blur\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 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([-31.2656], 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]: 0.8021,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 682:  46%|█▎ | 683/1495 [04:16<04:38,  2.92it/s]
[Running Accuracy]: 0.8023,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 683:  46%|████▌     | 683/1495 [04:16<04:38,  2.92it/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 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>How bright is this picture?
A. Bright
B. Fair
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Fair
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Fair\nC. Dark\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])
 C.

[Running Accuracy]: 0.8023,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 683:  46%|████▌     | 684/1495 [04:16<05:30,  2.45it/s]
[Running Accuracy]: 0.8026,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 684:  46%|████▌     | 684/1495 [04:16<05:30,  2.45it/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 bright is this picture?\nA. Bright\nB. Fair\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>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([-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]: 0.8026,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 684:  46%|████▌     | 685/1495 [04:17<05:23,  2.51it/s]
[Running Accuracy]: 0.8015,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 685:  46%|█████▍      | 685/1495 [04:17<05:23,  2.51it/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>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 object is related to the overexposed area in this image?
A. The worker
B. The car
C. The road
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is related to the overexposed area in this image?
A. The worker
B. The car
C. The road
Answer with the option's letter from the given choices directly.

prompts: [["Which object is related to the overexposed area in this image?\nA. The worker\nB. The car\nC. The road\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]: 0.8015,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 685:  46%|█████▌      | 686/1495 [04:17<05:01,  2.68it/s]
[Running Accuracy]: 0.8017,[Response]: B.<|endoftext|>, [Correct Ans]: The car, , [Prog]: 686:  46%|███▏   | 686/1495 [04:17<05:01,  2.68it/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>Which object is related to the overexposed area in this image?\nA. The worker\nB. The car\nC. The road\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

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

prompts: [["Is the airplane clear 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])
 B.

[Running Accuracy]: 0.8017,[Response]: B.<|endoftext|>, [Correct Ans]: The car, , [Prog]: 686:  46%|███▏   | 687/1495 [04:17<04:48,  2.80it/s]
[Running Accuracy]: 0.8020,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 687:  46%|█████      | 687/1495 [04:17<04:48,  2.80it/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>Is the airplane 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 is the color style of the image?
A. Purple
B. Gray
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color style of the image?
A. Purple
B. Gray
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["How is the color style of the image?\nA. Purple\nB. Gray\nC. Red\nD. Blue\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]: 0.8020,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 687:  46%|█████      | 688/1495 [04:18<04:38,  2.90it/s]
[Running Accuracy]: 0.8023,[Response]: A.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 688:  46%|███▋    | 688/1495 [04:18<04:38,  2.90it/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 color style of the image?\nA. Purple\nB. Gray\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>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([-30.9844], 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]: 0.8023,[Response]: A.<|endoftext|>, [Correct Ans]: Purple, , [Prog]: 688:  46%|███▋    | 689/1495 [04:18<04:37,  2.91it/s]
[Running Accuracy]: 0.8026,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 689:  46%|█████      | 689/1495 [04:18<04:37,  2.91it/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>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 generated by AI?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image generated by AI?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image generated by AI?\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]: 0.8026,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 689:  46%|█████      | 690/1495 [04:18<04:31,  2.97it/s]
[Running Accuracy]: 0.8029,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 690:  46%|█████      | 690/1495 [04:18<04:31,  2.97it/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>Is this 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>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([-31.2812], 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]: 0.8029,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 690:  46%|█████      | 691/1495 [04:19<04:21,  3.07it/s]
[Running Accuracy]: 0.8032,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 691:  46%|███▏   | 691/1495 [04:19<04:21,  3.07it/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 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': 'C.<|endoftext|>'} 

prompt A chat 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 picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers in this picture clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers in 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]: 0.8032,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 691:  46%|███▏   | 692/1495 [04:19<04:20,  3.08it/s]
[Running Accuracy]: 0.8020,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 692:  46%|█████▌      | 692/1495 [04:19<04:20,  3.08it/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>Are the flowers 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>Where is the brightest part of this picture?
A. Center
B. Surrounding
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the brightest part of this picture?
A. Center
B. Surrounding
Answer with the option's letter from the given choices directly.

prompts: [["Where is the brightest part of this picture?\nA. Center\nB. Surrounding\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]: 0.8020,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 692:  46%|█████▌      | 693/1495 [04:19<04:19,  3.09it/s]
[Running Accuracy]: 0.8023,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 693:  46%|███▋    | 693/1495 [04:19<04:19,  3.09it/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>Where is the brightest part 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 the horse in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the horse in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the horse in the image 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])
 B.

[Running Accuracy]: 0.8023,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 693:  46%|███▋    | 694/1495 [04:20<04:20,  3.08it/s]
[Running Accuracy]: 0.8012,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 694:  46%|█████▌      | 694/1495 [04:20<04:20,  3.08it/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>Is the horse 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>What is the worst distortion in this picture?
A. Motion blur
B. Brightness
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. Motion blur
B. Brightness
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. Motion blur\nB. Brightness\nC. Out of focus\nD. Overexposure\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]: 0.8012,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 694:  46%|█████▌      | 695/1495 [04:20<05:33,  2.40it/s]
[Running Accuracy]: 0.8014,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 695:  46%|▉ | 695/1495 [04:20<05:33,  2.40it/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>What is the worst distortion in this picture?\nA. Motion blur\nB. Brightness\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>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([-31.0156], 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]: 0.8014,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 695:  47%|▉ | 696/1495 [04:21<05:11,  2.56it/s]
[Running Accuracy]: 0.8003,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 696:  47%|█████      | 696/1495 [04:21<05:11,  2.56it/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>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 there a problem with image blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there a problem with image blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there a problem with image blur?\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]: 0.8003,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 696:  47%|█████▏     | 697/1495 [04:21<04:54,  2.71it/s]
[Running Accuracy]: 0.8006,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 697:  47%|█████▏     | 697/1495 [04:21<04:54,  2.71it/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>Is there a problem with image 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>What 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
What 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: [["What 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([-30.4062], 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]: 0.8006,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 697:  47%|█████▏     | 698/1495 [04:21<04:45,  2.79it/s]
[Running Accuracy]: 0.8009,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 698:  47%|██▊   | 698/1495 [04:21<04:45,  2.79it/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>What 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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 for 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 for 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 for 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([-31.2812], 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]: 0.8009,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 698:  47%|██▊   | 699/1495 [04:22<04:33,  2.91it/s]
[Running Accuracy]: 0.8011,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 699:  47%|▍| 699/1495 [04:22<04:33,  2.91it/
 {'prompt': "A chat between a curious 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 for 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>What is the worst distortion in this picture?
A. Out-of-focus
B. Underexposure
C. Motion blur
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. Motion blur
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. Motion blur\nD. 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])
 A.

[Running Accuracy]: 0.8011,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 699:  47%|▍| 700/1495 [04:22<05:08,  2.58it/
[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 700:  47%|▍| 700/1495 [04:22<05:08,  2.58it/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>What is the worst distortion in this picture?\nA. Out-of-focus\nB. Underexposure\nC. Motion blur\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 is the overall clarity of the image?
A. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall clarity of the image?
A. Bad
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of the image?\nA. Bad\nB. Fair\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])
 C.

[Running Accuracy]: 0.8000,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 700:  47%|▍| 701/1495 [04:23<05:03,  2.62it/s]
[Running Accuracy]: 0.7989,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 701:  47%|████▋     | 701/1495 [04:23<05:03,  2.62it/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 overall clarity of the 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>What is the main object in the image?
A. Eiffel Tower
B. Fountain
C. Pedestrians
D. Road
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main object in the image?
A. Eiffel Tower
B. Fountain
C. Pedestrians
D. Road
Answer with the option's letter from the given choices directly.

prompts: [["What is the main object in the image?\nA. Eiffel Tower\nB. Fountain\nC. Pedestrians\nD. Road\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]: 0.7989,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 701:  47%|████▋     | 702/1495 [04:23<04:48,  2.75it/s]
[Running Accuracy]: 0.7991,[Response]: A.<|endoftext|>, [Correct Ans]: Eiffel Tower, , [Prog]: 702:  47%|▉ | 702/1495 [04:23<04:48,  2.75it/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>What is the main object in the image?\nA. Eiffel Tower\nB. Fountain\nC. Pedestrians\nD. Road\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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 fish fin rich in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the fish fin rich in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the fish fin rich in the image?\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])
 B.

[Running Accuracy]: 0.7991,[Response]: A.<|endoftext|>, [Correct Ans]: Eiffel Tower, , [Prog]: 702:  47%|▉ | 703/1495 [04:23<04:43,  2.79it/s]
[Running Accuracy]: 0.7994,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 703:  47%|█████▋      | 703/1495 [04:23<04:43,  2.79it/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>Is the color of the fish fin rich 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 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([-30.6406], 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]: 0.7994,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 703:  47%|█████▋      | 704/1495 [04:24<04:37,  2.85it/s]
[Running Accuracy]: 0.7983,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 704:  47%|▉ | 704/1495 [04:24<04:37,  2.85it/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>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>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([-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]: 0.7983,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 704:  47%|▉ | 705/1495 [04:24<04:27,  2.96it/s]
[Running Accuracy]: 0.7986,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 705:  47%|█████▏     | 705/1495 [04:24<04:27,  2.96it/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>Is the image motion-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>How is the clarity of the image?
A. Poor
B. Good
C. Acceptable
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. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Poor\nB. Good\nC. Acceptable\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]: 0.7986,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 705:  47%|█████▏     | 706/1495 [04:24<05:22,  2.44it/s]
[Running Accuracy]: 0.7989,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 706:  47%|████▋     | 706/1495 [04:24<05:22,  2.44it/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 clarity of the image?\nA. Poor\nB. Good\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 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([-31.0156], 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]: 0.7989,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 706:  47%|████▋     | 707/1495 [04:25<04:58,  2.64it/s]
[Running Accuracy]: 0.7977,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 707:  47%|█████▏     | 707/1495 [04:25<04:58,  2.64it/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>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>Which part of the image has the highest brightness?
A. Face
B. Tie
C. Hand
D. Shoulder
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image has the highest brightness?
A. Face
B. Tie
C. Hand
D. Shoulder
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image has the highest brightness?\nA. Face\nB. Tie\nC. Hand\nD. Shoulder\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]: 0.7977,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 707:  47%|█████▏     | 708/1495 [04:25<04:44,  2.76it/s]
[Running Accuracy]: 0.7966,[Response]: B.<|endoftext|>, [Correct Ans]: Face, , [Prog]: 708:  47%|████▋     | 708/1495 [04:25<04:44,  2.76it/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>Which part of the image has the highest brightness?\nA. Face\nB. Tie\nC. Hand\nD. Shoulder\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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([-30.8906], 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]: 0.7966,[Response]: B.<|endoftext|>, [Correct Ans]: Face, , [Prog]: 708:  47%|████▋     | 709/1495 [04:25<04:33,  2.87it/s]
[Running Accuracy]: 0.7955,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 709:  47%|█████▏     | 709/1495 [04:25<04:33,  2.87it/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>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 blurry is the tree in the image?
A. Very blurry
B. Not blurry at all
C. Slightly 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. Slightly 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. Slightly 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])
 A.

[Running Accuracy]: 0.7955,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 709:  47%|█████▏     | 710/1495 [04:26<04:26,  2.95it/s]
[Running Accuracy]: 0.7944,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 710:  47%|▍| 710/1495 [04:26<04:26,  2.95it/
 {'prompt': "A chat between 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. Slightly 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 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([-31.3906], 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]: 0.7944,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 710:  48%|▍| 711/1495 [04:26<04:19,  3.03it/
[Running Accuracy]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 711:  48%|████▊     | 711/1495 [04:26<04:19,  3.03it/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 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 distortion does this image mainly suffer?
A. Noise
B. Overexposure
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. Overexposure
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. Overexposure\nC. Blurriness\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]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 711:  48%|████▊     | 712/1495 [04:26<04:07,  3.17it/s]
[Running Accuracy]: 0.7949,[Response]: A<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 712:  48%|████▊     | 712/1495 [04:26<04:07,  3.17it/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>What kind of distortion does this image mainly suffer?\nA. Noise\nB. Overexposure\nC. Blurriness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A<|endoftext|>'} 

prompt A chat between 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 trees 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 trees 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 trees in this picture?\nA. Blurry\nB. Clear\nC. Normal\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])
 B.

[Running Accuracy]: 0.7949,[Response]: A<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 712:  48%|████▊     | 713/1495 [04:27<04:12,  3.09it/s]
[Running Accuracy]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 713:  48%|███▊    | 713/1495 [04:27<04:12,  3.09it/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 clear are the trees 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 is the main color scheme of the image?
A. Black and white
B. White
C. Colorless
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main color scheme of the image?
A. Black and white
B. White
C. Colorless
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the main color scheme of the image?\nA. Black and white\nB. White\nC. Colorless\nD. Black\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]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 713:  48%|███▊    | 714/1495 [04:27<04:09,  3.13it/s]
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Black and white, , [Prog]: 714:  48%|▍| 714/1495 [04:27<04:09,  3.13it/
 {'prompt': "A chat between a curious 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. Black and white\nB. White\nC. Colorless\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>What 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 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 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([-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]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Black and white, , [Prog]: 714:  48%|▍| 715/1495 [04:27<04:11,  3.11it/
[Running Accuracy]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 715:  48%|▍| 715/1495 [04:27<04:11,  3.11it/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>What 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>Which object is emphasized in the composition of the image?
A. Creek
B. Stone
C. Grass
D. Trees
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. Creek
B. Stone
C. Grass
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Creek\nB. Stone\nC. Grass\nD. Trees\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]: 0.7944,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 715:  48%|▍| 716/1495 [04:28<04:08,  3.14it/s]
[Running Accuracy]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Creek, , [Prog]: 716:  48%|████▎    | 716/1495 [04:28<04:08,  3.14it/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>Which object is emphasized in the composition of the image?\nA. Creek\nB. Stone\nC. Grass\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 is the most apparent distortion of the signs on the top 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 the signs on the top 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 the signs on the top 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([-31.0312], 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]: 0.7947,[Response]: A.<|endoftext|>, [Correct Ans]: Creek, , [Prog]: 716:  48%|████▎    | 717/1495 [04:28<04:07,  3.15it/s]
[Running Accuracy]: 0.7950,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 717:  48%|▍| 717/1495 [04:28<04:07,  3.15it/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>What is the most apparent distortion of the signs on the top 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': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 car in 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 color saturation of the car in the 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 the car in the image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6562], 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]: 0.7950,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 717:  48%|▍| 718/1495 [04:28<04:08,  3.13it/s]
[Running Accuracy]: 0.7953,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 718:  48%|████▊     | 718/1495 [04:28<04:08,  3.13it/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 color saturation of the car in 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>How clear are the characters in the image?
A. Recognizable, but not clear
B. Very clear
C. Not recognizable at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters in the image?
A. Recognizable, but not clear
B. Very clear
C. Not recognizable at all
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters in the image?\nA. Recognizable, but not clear\nB. Very clear\nC. Not recognizable 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]: 0.7953,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 718:  48%|████▊     | 719/1495 [04:29<05:31,  2.34it/s]
[Running Accuracy]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Recognizable, but not clear, , [Prog]: 719:  48%|▍| 719/1495 [04:29<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 clear are the characters in the image?\nA. Recognizable, but not clear\nB. Very clear\nC. Not recognizable 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>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([-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]: 0.7955,[Response]: A.<|endoftext|>, [Correct Ans]: Recognizable, but not clear, , [Prog]: 719:  48%|▍| 720/1495 [04:29<05:
[Running Accuracy]: 0.7958,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 720:  48%|█████▊      | 720/1495 [04:29<05:01,  2.57it/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>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 is the lighting of the sky 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 sky 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 sky in this image?\nA. Dark\nB. Medium\nC. Bright\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]: 0.7958,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 720:  48%|█████▊      | 721/1495 [04:30<04:55,  2.62it/s]
[Running Accuracy]: 0.7947,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 721:  48%|████▊     | 721/1495 [04:30<04:55,  2.62it/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 lighting of the sky 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>How is the clarity of the tree in 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 clarity of the tree in this image?
A. High
B. Low
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the tree in this image?\nA. High\nB. Low\nC. Acceptable\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]: 0.7947,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 721:  48%|████▊     | 722/1495 [04:30<04:40,  2.75it/s]
[Running Accuracy]: 0.7950,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 722:  48%|█████▎     | 722/1495 [04:30<04:40,  2.75it/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 clarity of the tree 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>Is the building emphasized in the center of the composition in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the building emphasized in the center of the composition in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the building emphasized in the center of the composition 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]: 0.7950,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 722:  48%|█████▎     | 723/1495 [04:30<04:29,  2.87it/s]
[Running Accuracy]: 0.7953,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 723:  48%|█████▎     | 723/1495 [04:30<04:29,  2.87it/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>Is the building emphasized in the center of the composition 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's the focus of this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus of this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus of this image?\nA. Medium\nB. Good\nC. Poor\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]: 0.7953,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 723:  48%|█████▎     | 724/1495 [04:30<04:24,  2.91it/s]
[Running Accuracy]: 0.7956,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 724:  48%|████▊     | 724/1495 [04:30<04:24,  2.91it/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's the focus of this image?\nA. Medium\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 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([-30.1875], 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]: 0.7956,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 724:  48%|████▊     | 725/1495 [04:31<05:26,  2.36it/s]
[Running Accuracy]: 0.7959,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 725:  48%|█████▎     | 725/1495 [04:31<05:26,  2.36it/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>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 major distortion of the giraffe 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 giraffe 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 giraffe in this image?\nA. Noise\nB. Blur\nC. Over-exposure\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]: 0.7959,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 725:  49%|█████▎     | 726/1495 [04:31<05:04,  2.53it/s]
[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 726:  49%|████▊     | 726/1495 [04:31<05:04,  2.53it/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>What is the major distortion of the giraffe in this image?\nA. Noise\nB. 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>Is the primary light source in the image sunlight?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the primary light source in the image sunlight?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the primary light source in the image sunlight?\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])
 A.

[Running Accuracy]: 0.7961,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 726:  49%|████▊     | 727/1495 [04:32<04:46,  2.68it/s]
[Running Accuracy]: 0.7964,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 727:  49%|█████▎     | 727/1495 [04:32<04:46,  2.68it/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>Is the primary light source in the image sunlight?\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 come in the image?
A. Top
B. Right
C. Bottom
D. Left
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light come in the image?
A. Top
B. Right
C. Bottom
D. Left
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light come in the image?\nA. Top\nB. Right\nC. Bottom\nD. Left\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]: 0.7964,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 727:  49%|█████▎     | 728/1495 [04:32<04:35,  2.79it/s]
[Running Accuracy]: 0.7953,[Response]: B.<|endoftext|>, [Correct Ans]: Left, , [Prog]: 728:  49%|████▊     | 728/1495 [04:32<04:35,  2.79it/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>From which direction does the light come in the image?\nA. Top\nB. Right\nC. Bottom\nD. Left\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 the image?
A. The groud
B. The flower
C. The wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main focus of the image?
A. The groud
B. The flower
C. The wall
Answer with the option's letter from the given choices directly.

prompts: [["What is the main focus of the image?\nA. The groud\nB. The flower\nC. The wall\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]: 0.7953,[Response]: B.<|endoftext|>, [Correct Ans]: Left, , [Prog]: 728:  49%|████▉     | 729/1495 [04:33<05:05,  2.50it/s]
[Running Accuracy]: 0.7956,[Response]: B.<|endoftext|>, [Correct Ans]: The flower, , [Prog]: 729:  49%|█▉  | 729/1495 [04:33<05:05,  2.50it/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>What is the main focus of the image?\nA. The groud\nB. The flower\nC. The 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 kind of feeling does the image evoke?
A. Depressed
B. Pleasant
C. Dull
D. Sad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does the image evoke?
A. Depressed
B. Pleasant
C. Dull
D. Sad
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does the image evoke?\nA. Depressed\nB. Pleasant\nC. Dull\nD. Sad\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]: 0.7956,[Response]: B.<|endoftext|>, [Correct Ans]: The flower, , [Prog]: 729:  49%|█▉  | 730/1495 [04:33<04:46,  2.67it/s]
[Running Accuracy]: 0.7959,[Response]: B.<|endoftext|>, [Correct Ans]: Pleasant, , [Prog]: 730:  49%|██▉   | 730/1495 [04:33<04:46,  2.67it/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>What kind of feeling does the image evoke?\nA. Depressed\nB. Pleasant\nC. Dull\nD. Sad\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image centered?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image centered?\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]: 0.7959,[Response]: B.<|endoftext|>, [Correct Ans]: Pleasant, , [Prog]: 730:  49%|██▉   | 731/1495 [04:33<04:33,  2.79it/s]
[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 731:  49%|█████▊      | 731/1495 [04:33<04:33,  2.79it/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>Is the composition of this image centered?\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 man's face on the left side of the image?
A. Poor
B. Very good
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the man's face on the left side of the image?
A. Poor
B. Very good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the man's face on the left side of the image?\nA. Poor\nB. Very good\nC. Average\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]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 731:  49%|█████▉      | 732/1495 [04:34<04:28,  2.85it/s]
[Running Accuracy]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: Very good, , [Prog]: 732:  49%|██▍  | 732/1495 [04:34<04:28,  2.85it/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 clear is the man's face on the left side of the image?\nA. Poor\nB. Very 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>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([-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]: 0.7951,[Response]: B.<|endoftext|>, [Correct Ans]: Very good, , [Prog]: 732:  49%|██▍  | 733/1495 [04:34<04:18,  2.95it/s]
[Running Accuracy]: 0.7940,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 733:  49%|████▉     | 733/1495 [04:34<04:18,  2.95it/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 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 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([-31.0156], 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]: 0.7940,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 733:  49%|████▉     | 734/1495 [04:34<04:15,  2.98it/s]
[Running Accuracy]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 734:  49%|█████▉      | 734/1495 [04:34<04:15,  2.98it/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>Is this image 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>What is the most apparent distortion of the boy 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 most apparent distortion of the boy 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 most apparent distortion of the boy in this image?\nA. Over-exposure\nB. Blur\nC. Noise\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]: 0.7943,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 734:  49%|█████▉      | 735/1495 [04:34<04:09,  3.04it/s]
[Running Accuracy]: 0.7946,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 735:  49%|████▍    | 735/1495 [04:34<04:09,  3.04it/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>What is the most apparent distortion of the boy in this image?\nA. Over-exposure\nB. Blur\nC. 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>Does this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0938], 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]: 0.7946,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 735:  49%|████▍    | 736/1495 [04:35<04:04,  3.10it/s]
[Running Accuracy]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 736:  49%|█████▍     | 736/1495 [04:35<04:04,  3.10it/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>Does 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 will you rate the clarity of the image?
A. Good
B. Average
C. Terrible
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How will you rate the clarity of the image?
A. Good
B. Average
C. Terrible
Answer with the option's letter from the given choices directly.

prompts: [["How will you rate the clarity of the image?\nA. Good\nB. Average\nC. Terrible\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]: 0.7948,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 736:  49%|█████▍     | 737/1495 [04:35<04:03,  3.11it/s]
[Running Accuracy]: 0.7951,[Response]: C.<|endoftext|>, [Correct Ans]: Terrible, , [Prog]: 737:  49%|██▉   | 737/1495 [04:35<04:03,  3.11it/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 will you rate the clarity of the image?\nA. Good\nB. Average\nC. Terrible\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 of 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 problem of compression distortion in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any problem of compression distortion 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])
 A.

[Running Accuracy]: 0.7951,[Response]: C.<|endoftext|>, [Correct Ans]: Terrible, , [Prog]: 737:  49%|██▉   | 738/1495 [04:35<04:01,  3.13it/s]
[Running Accuracy]: 0.7940,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 738:  49%|█████▍     | 738/1495 [04:35<04:01,  3.13it/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>Is there any problem of 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>What is the clearest part of this image?
A. Sky
B. Animal
C. Rock
D. Mountains
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part of this image?
A. Sky
B. Animal
C. Rock
D. Mountains
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part of this image?\nA. Sky\nB. Animal\nC. Rock\nD. Mountains\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]: 0.7940,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 738:  49%|█████▍     | 739/1495 [04:36<04:06,  3.07it/s]
[Running Accuracy]: 0.7943,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 739:  49%|█████▍     | 739/1495 [04:36<04:06,  3.07it/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>What is the clearest part of this image?\nA. Sky\nB. Animal\nC. Rock\nD. Mountains\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 there with the image?
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 problems are there with the image?
A. Overexposure
B. Out of focus
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What problems are there with the image?\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([-30.9688], 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]: 0.7943,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 739:  49%|█████▍     | 740/1495 [04:36<04:02,  3.11it/s]
[Running Accuracy]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 740:  49%|▉ | 740/1495 [04:36<04:02,  3.11it/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>What problems are there with the image?\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': 'A.<|endoftext|>'} 

prompt A chat between 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 does not appear in this image?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion does not appear in this image?
A. Blur
B. Under-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion does not appear in this image?\nA. Blur\nB. Under-exposure\nC. Noise\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]: 0.7946,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 740:  50%|▉ | 741/1495 [04:36<04:00,  3.14it/s]
[Running Accuracy]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 741:  50%|████▍    | 741/1495 [04:36<04:00,  3.14it/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>Which distortion does not appear in 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>What is the lighting condition about the image?
A. Too dark
B. Too bright
C. Just fine
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the lighting condition about the image?
A. Too dark
B. Too bright
C. Just fine
Answer with the option's letter from the given choices directly.

prompts: [["What is the lighting condition about the image?\nA. Too dark\nB. Too bright\nC. Just fine\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]: 0.7935,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 741:  50%|████▍    | 742/1495 [04:37<04:06,  3.06it/s]
[Running Accuracy]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 742:  50%|█▉  | 742/1495 [04:37<04:06,  3.06it/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>What is the lighting condition about the image?\nA. Too dark\nB. Too bright\nC. Just fine\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 the human part in the image bright?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting of the human part in the image bright?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting of the human part in the image bright?\nA. Bright\nB. Dark\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])
 A.

[Running Accuracy]: 0.7938,[Response]: B.<|endoftext|>, [Correct Ans]: Too bright, , [Prog]: 742:  50%|█▉  | 743/1495 [04:37<04:06,  3.05it/s]
[Running Accuracy]: 0.7927,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 743:  50%|████▉     | 743/1495 [04:37<04:06,  3.05it/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>Is the lighting of the human part in the image bright?\nA. Bright\nB. Dark\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 lighting of the cat 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 of the cat 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 of the cat in this image?\nA. Medium\nB. High\nC. Low\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]: 0.7927,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 743:  50%|████▉     | 744/1495 [04:37<04:05,  3.06it/s]
[Running Accuracy]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 744:  50%|█████▍     | 744/1495 [04:37<04:05,  3.06it/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 lighting of the cat 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>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([-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]: 0.7930,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 744:  50%|█████▍     | 745/1495 [04:38<04:06,  3.05it/s]
[Running Accuracy]: 0.7933,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 745:  50%|█████▉      | 745/1495 [04:38<04:06,  3.05it/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>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>How is the richness of colors 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 richness of colors in the image?
A. Rich
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the richness of colors in the image?\nA. Rich\nB. Monotonous\nC. Medium\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]: 0.7933,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 745:  50%|█████▉      | 746/1495 [04:38<04:08,  3.02it/s]
[Running Accuracy]: 0.7936,[Response]: A.<|endoftext|>, [Correct Ans]: Rich, , [Prog]: 746:  50%|████▉     | 746/1495 [04:38<04:08,  3.02it/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 richness of colors in the image?\nA. Rich\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>Which part of the image is emphasized in its composition?
A. Trees
B. Leopard
C. Human
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is emphasized in its composition?
A. Trees
B. Leopard
C. Human
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is emphasized in its composition?\nA. Trees\nB. Leopard\nC. Human\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]: 0.7936,[Response]: A.<|endoftext|>, [Correct Ans]: Rich, , [Prog]: 746:  50%|████▉     | 747/1495 [04:38<04:11,  2.98it/s]
[Running Accuracy]: 0.7938,[Response]: C.<|endoftext|>, [Correct Ans]: Human, , [Prog]: 747:  50%|████▍    | 747/1495 [04:38<04:11,  2.98it/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>Which part of the image is emphasized in its composition?\nA. Trees\nB. Leopard\nC. Human\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat 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 kitten 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 kitten 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 kitten emphasized in the center?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.9688], 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]: 0.7938,[Response]: C.<|endoftext|>, [Correct Ans]: Human, , [Prog]: 747:  50%|████▌    | 748/1495 [04:39<04:04,  3.05it/s]
[Running Accuracy]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 748:  50%|█████▌     | 748/1495 [04:39<04:04,  3.05it/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>In the composition of the image, is the kitten 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 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([-30.9219], 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]: 0.7941,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 748:  50%|█████▌     | 749/1495 [04:39<04:05,  3.04it/s]
[Running Accuracy]: 0.7944,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 749:  50%|█████▌     | 749/1495 [04:39<04:05,  3.04it/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>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>What is the most apparent distortion of 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 most apparent distortion of this image?
A. Over-exposure
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. Over-exposure\nB. Blur\nC. 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]: 0.7944,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 749:  50%|█████▌     | 750/1495 [04:39<04:02,  3.08it/s]
[Running Accuracy]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 750:  50%|█████     | 750/1495 [04:39<04:02,  3.08it/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>What is the most apparent distortion of 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 sharpest object in the image?
A. Lemon slice
B. Straw
C. Person
D. Cup
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest object in the image?
A. Lemon slice
B. Straw
C. Person
D. Cup
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest object in the image?\nA. Lemon slice\nB. Straw\nC. Person\nD. Cup\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]: 0.7947,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 750:  50%|█████     | 751/1495 [04:40<04:03,  3.05it/s]
[Running Accuracy]: 0.7936,[Response]: A.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 751:  50%|█████▌     | 751/1495 [04:40<04:03,  3.05it/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>What is the sharpest object in the image?\nA. Lemon slice\nB. Straw\nC. Person\nD. Cup\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Is the boy wearing a red hat 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 boy wearing a red hat 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 boy wearing a red hat 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([-31.1094], 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]: 0.7936,[Response]: A.<|endoftext|>, [Correct Ans]: Cup, , [Prog]: 751:  50%|█████▌     | 752/1495 [04:40<04:02,  3.06it/s]
[Running Accuracy]: 0.7926,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 752:  50%|██████      | 752/1495 [04:40<04:02,  3.06it/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>Is the boy wearing a red hat 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 sharpness of the wine glass in 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 sharpness of the wine glass in the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the wine glass in the image?\nA. Good\nB. Poor\nC. Fair\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]: 0.7926,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 752:  50%|██████      | 753/1495 [04:40<03:59,  3.10it/s]
[Running Accuracy]: 0.7928,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 753:  50%|█████     | 753/1495 [04:40<03:59,  3.10it/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 sharpness of the wine glass in 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>How clear is thie children in this picture?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is thie children in this picture?
A. Clear
B. Blurry
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How clear is thie children in this picture?\nA. Clear\nB. Blurry\nC. Average\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]: 0.7928,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 753:  50%|█████     | 754/1495 [04:41<05:07,  2.41it/s]
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 754:  50%|████    | 754/1495 [04:41<05:07,  2.41it/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 clear is thie children in this picture?\nA. Clear\nB. Blurry\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>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([-31.2188], 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]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 754:  51%|████    | 755/1495 [04:41<04:50,  2.55it/s]
[Running Accuracy]: 0.7921,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 755:  51%|██████      | 755/1495 [04:41<04:50,  2.55it/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>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>Which object is emphasized in the composition of the image?
A. Cow
B. Grass
C. Light
D. Trees
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. Cow
B. Grass
C. Light
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Cow\nB. Grass\nC. Light\nD. Trees\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]: 0.7921,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 755:  51%|██████      | 756/1495 [04:42<04:33,  2.71it/s]
[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Cow, , [Prog]: 756:  51%|█████▌     | 756/1495 [04:42<04:33,  2.71it/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>Which object is emphasized in the composition of the image?\nA. Cow\nB. Grass\nC. Light\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>Is the main subject not well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject not well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject not well-defined?\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]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Cow, , [Prog]: 756:  51%|█████▌     | 757/1495 [04:42<04:20,  2.83it/s]
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 757:  51%|██████      | 757/1495 [04:42<04:20,  2.83it/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>Is the main subject not well-defined?\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 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([-31.2344], 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]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 757:  51%|██████      | 758/1495 [04:42<04:14,  2.90it/s]
[Running Accuracy]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 758:  51%|█████▌     | 758/1495 [04:42<04:14,  2.90it/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 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 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])
 A.

[Running Accuracy]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 758:  51%|█████▌     | 759/1495 [04:43<04:10,  2.94it/s]
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 759:  51%|████    | 759/1495 [04:43<04:10,  2.94it/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 lighting of this image?\nA. Medium\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>Is the hand of the woman in the left in motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the hand of the woman in the left in motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the hand of the woman in the left in motion blur?\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]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 759:  51%|████    | 760/1495 [04:43<04:06,  2.98it/s]
[Running Accuracy]: 0.7921,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 760:  51%|█████▌     | 760/1495 [04:43<04:06,  2.98it/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>Is the hand of the woman in the left in 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>Which part is still relatively clear in this image?
A. Head of the person
B. Shirt of the person
C. The wall
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part is still relatively clear in this image?
A. Head of the person
B. Shirt of the person
C. The wall
Answer with the option's letter from the given choices directly.

prompts: [["Which part is still relatively clear in this image?\nA. Head of the person\nB. Shirt of the person\nC. The wall\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]: 0.7921,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 760:  51%|█████▌     | 761/1495 [04:43<04:03,  3.02it/s]
[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Shirt of the person, , [Prog]: 761:  51%|▌| 761/1495 [04:43<04:03,  3.0
 {'prompt': "A chat between 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 still relatively clear in this image?\nA. Head of the person\nB. Shirt of the person\nC. The wall\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Spaceship
B. Soldier
C. Ground
D. Red cloth
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most vibrant color in the image?
A. Spaceship
B. Soldier
C. Ground
D. Red cloth
Answer with the option's letter from the given choices directly.

prompts: [["What is the most vibrant color in the image?\nA. Spaceship\nB. Soldier\nC. Ground\nD. Red cloth\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]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: Shirt of the person, , [Prog]: 761:  51%|▌| 762/1495 [04:44<04:07,  2.9
[Running Accuracy]: 0.7913,[Response]: D.<|endoftext|>, [Correct Ans]: Red cloth, , [Prog]: 762:  51%|██▌  | 762/1495 [04:44<04:07,  2.97it/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>What is the most vibrant color in the image?\nA. Spaceship\nB. Soldier\nC. Ground\nD. Red cloth\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 in the image appears darkest?
A. Dog
B. Utility pole
C. Figure
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image appears darkest?
A. Dog
B. Utility pole
C. Figure
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image appears darkest?\nA. Dog\nB. Utility pole\nC. Figure\nD. Trees\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]: 0.7913,[Response]: D.<|endoftext|>, [Correct Ans]: Red cloth, , [Prog]: 762:  51%|██▌  | 763/1495 [04:44<04:05,  2.99it/s]
[Running Accuracy]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 763:  51%|█████▌     | 763/1495 [04:44<04:05,  2.99it/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>Which object in the image appears darkest?\nA. Dog\nB. Utility pole\nC. Figure\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's the worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Overexposure
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. Underexposure
B. Out of focus
C. Overexposure
D. Motion blur
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. Overexposure\nD. 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])
 A.

[Running Accuracy]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 763:  51%|█████▌     | 764/1495 [04:44<04:00,  3.04it/s]
[Running Accuracy]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 764:  51%|█ | 764/1495 [04:44<04:00,  3.04it/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>What's the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\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>What is the brightest part in this photo?
A. Trees
B. Sky
C. Rocks
D. People
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this photo?
A. Trees
B. Sky
C. Rocks
D. People
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this photo?\nA. Trees\nB. Sky\nC. Rocks\nD. People\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]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 764:  51%|█ | 765/1495 [04:45<04:02,  3.01it/s]
[Running Accuracy]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 765:  51%|█████▋     | 765/1495 [04:45<04:02,  3.01it/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>What is the brightest part in this photo?\nA. Trees\nB. Sky\nC. Rocks\nD. People\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 plant in 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 plant in this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How bright is the plant in this picture?\nA. Normal\nB. Dark\nC. Bright\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]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 765:  51%|█████▋     | 766/1495 [04:45<04:52,  2.49it/s]
[Running Accuracy]: 0.7911,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 766:  51%|█████     | 766/1495 [04:45<04:52,  2.49it/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 bright is the plant in 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>Which of the following quality issues does the image not have?
A. Motion blur
B. Compression distortion
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 the image not have?
A. Motion blur
B. Compression distortion
C. Underexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following quality issues does the image not have?\nA. Motion blur\nB. Compression distortion\nC. Underexposure\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])
 B.

[Running Accuracy]: 0.7911,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 766:  51%|█████▏    | 767/1495 [04:45<04:33,  2.66it/s]
[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 767:  51%|▌| 767/1495 [04:45<04:33,  2.66it/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>Which of the following quality issues does the image not have?\nA. Motion blur\nB. Compression distortion\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 clearest object in the image?
A. Grassland
B. Forest
C. Bird
D. Branch
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Grassland
B. Forest
C. Bird
D. Branch
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Grassland\nB. Forest\nC. Bird\nD. Branch\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]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 767:  51%|▌| 768/1495 [04:46<04:21,  2.78it/s]
[Running Accuracy]: 0.7904,[Response]: C.<|endoftext|>, [Correct Ans]: Bird, , [Prog]: 768:  51%|█████▏    | 768/1495 [04:46<04:21,  2.78it/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>What is the clearest object in the image?\nA. Grassland\nB. Forest\nC. Bird\nD. Branch\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat 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 come in the image?
A. Left
B. Right
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light come in the image?
A. Left
B. Right
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light come in the image?\nA. Left\nB. Right\nC. Top\nD. Bottom\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]: 0.7904,[Response]: C.<|endoftext|>, [Correct Ans]: Bird, , [Prog]: 768:  51%|█████▏    | 769/1495 [04:46<04:11,  2.88it/s]
[Running Accuracy]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Left, , [Prog]: 769:  51%|█████▏    | 769/1495 [04:46<04:11,  2.88it/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>From which direction does the light come in the image?\nA. Left\nB. Right\nC. Top\nD. Bottom\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 colorful object in the image?
A. Butterfly
B. Leaf
C. Flower
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most colorful object in the image?
A. Butterfly
B. Leaf
C. Flower
Answer with the option's letter from the given choices directly.

prompts: [["What is the most colorful object in the image?\nA. Butterfly\nB. Leaf\nC. Flower\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]: 0.7893,[Response]: C.<|endoftext|>, [Correct Ans]: Left, , [Prog]: 769:  52%|█████▏    | 770/1495 [04:46<04:05,  2.96it/s]
[Running Accuracy]: 0.7883,[Response]: C.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 770:  52%|██▌  | 770/1495 [04:46<04:05,  2.96it/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>What is the most colorful object in the image?\nA. Butterfly\nB. Leaf\nC. Flower\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 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 contrast 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 contrast of the image?\nA. Low\nB. Medium\nC. High\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]: 0.7883,[Response]: C.<|endoftext|>, [Correct Ans]: Butterfly, , [Prog]: 770:  52%|██▌  | 771/1495 [04:47<03:56,  3.07it/s]
[Running Accuracy]: 0.7886,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 771:  52%|█████▋     | 771/1495 [04:47<03:56,  3.07it/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 brightness contrast of the 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 is the worst distortion in this picture?
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 is the worst distortion in this picture?
A. Overexposure
B. Motion blur
C. Noise
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. Motion blur\nC. Noise\nD. Out of focus\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]: 0.7886,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 771:  52%|█████▋     | 772/1495 [04:47<05:17,  2.28it/s]
[Running Accuracy]: 0.7889,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 772:  52%|█ | 772/1495 [04:47<05:17,  2.28it/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>What is the worst distortion in this picture?\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': '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 are there with this image?
A. Out of focus
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems are there with this image?
A. Out of focus
B. Motion blur
C. Overexposure
D. Compression artifacts
Answer with the option's letter from the given choices directly.

prompts: [["What problems are there with this image?\nA. Out of focus\nB. Motion blur\nC. Overexposure\nD. Compression artifacts\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]: 0.7889,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 772:  52%|█ | 773/1495 [04:48<04:49,  2.49it/s]
[Running Accuracy]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 773:  52%|█ | 773/1495 [04:48<04:49,  2.49it/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>What problems are there with this image?\nA. Out of focus\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 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([-30.9688], 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]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 773:  52%|█ | 774/1495 [04:48<05:29,  2.19it/s]
[Running Accuracy]: 0.7894,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 774:  52%|█████▏    | 774/1495 [04:48<05:29,  2.19it/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 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>What is the most vibrant in the image?
A. Accessories
B. Eyes
C. Clothes
D. Hair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most vibrant in the image?
A. Accessories
B. Eyes
C. Clothes
D. Hair
Answer with the option's letter from the given choices directly.

prompts: [["What is the most vibrant in the image?\nA. Accessories\nB. Eyes\nC. Clothes\nD. Hair\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]: 0.7894,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 774:  52%|█████▏    | 775/1495 [04:49<05:01,  2.39it/s]
[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: Eyes, , [Prog]: 775:  52%|█████▏    | 775/1495 [04:49<05:01,  2.39it/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>What is the most vibrant in the image?\nA. Accessories\nB. Eyes\nC. Clothes\nD. 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>What is the brightest part in this image?
A. Table
B. Man with a hat
C. Man without a hat
D. Cup
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Table
B. Man with a hat
C. Man without a hat
D. Cup
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Table\nB. Man with a hat\nC. Man without a hat\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])
 A.

[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: Eyes, , [Prog]: 775:  52%|█████▏    | 776/1495 [04:49<04:38,  2.58it/s]
[Running Accuracy]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: Man without a hat, , [Prog]: 776:  52%|▌| 776/1495 [04:49<04:38,  2.58i
 {'prompt': "A chat between a curious 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. Table\nB. Man with a hat\nC. Man without a hat\nD. Cup\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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. Backlighting
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. Backlighting
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. Backlighting\nB. Underexposure\nC. Motion blur\nD. Compression artifacts\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]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: Man without a hat, , [Prog]: 776:  52%|▌| 777/1495 [04:49<04:22,  2.73i
[Running Accuracy]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 777:  52%|█ | 777/1495 [04:49<04:22,  2.73it/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>What problems exist in the image?\nA. Backlighting\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>Which image quality problem exists in the image?
A. Motion blur
B. Overexposure
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image quality problem exists in the image?
A. Motion blur
B. Overexposure
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which image quality problem exists in the image?\nA. Motion blur\nB. Overexposure\nC. Distortion\nD. Underexposure\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])
 A.

[Running Accuracy]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Backlighting, , [Prog]: 777:  52%|█ | 778/1495 [04:50<04:09,  2.87it/s]
[Running Accuracy]: 0.7879,[Response]: A.<|endoftext|>, [Correct Ans]: Distortion, , [Prog]: 778:  52%|██  | 778/1495 [04:50<04:09,  2.87it/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>Which image quality problem exists in the image?\nA. Motion blur\nB. Overexposure\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>Which object in this image is in focus?
A. Ground
B. Grass
C. Duck
D. Pebbles
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is in focus?
A. Ground
B. Grass
C. Duck
D. Pebbles
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is in focus?\nA. Ground\nB. Grass\nC. Duck\nD. Pebbles\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]: 0.7879,[Response]: A.<|endoftext|>, [Correct Ans]: Distortion, , [Prog]: 778:  52%|██  | 779/1495 [04:50<04:06,  2.90it/s]
[Running Accuracy]: 0.7882,[Response]: C.<|endoftext|>, [Correct Ans]: Duck, , [Prog]: 779:  52%|█████▏    | 779/1495 [04:50<04:06,  2.90it/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>Which object in this image is in focus?\nA. Ground\nB. Grass\nC. Duck\nD. Pebbles\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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([-31.2656], 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]: 0.7882,[Response]: C.<|endoftext|>, [Correct Ans]: Duck, , [Prog]: 779:  52%|█████▏    | 780/1495 [04:50<04:03,  2.93it/s]
[Running Accuracy]: 0.7872,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 780:  52%|████▏   | 780/1495 [04:50<04:03,  2.93it/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 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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 fruits?
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 fruits?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the fruits?\nA. Good\nB. Poor\nC. Fair\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]: 0.7872,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 780:  52%|████▏   | 781/1495 [04:51<03:56,  3.01it/s]
[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 781:  52%|█████▏    | 781/1495 [04:51<03:56,  3.01it/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 clarity of the fruits?\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>Are the buildings colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the buildings colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the buildings colorful?\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]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 781:  52%|█████▏    | 782/1495 [04:51<04:04,  2.92it/s]
[Running Accuracy]: 0.7877,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 782:  52%|██████▎     | 782/1495 [04:51<04:04,  2.92it/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>Are the buildings 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 image of high quality?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image of high quality?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image of high quality?\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]: 0.7877,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 782:  52%|██████▎     | 783/1495 [04:51<04:02,  2.94it/s]
[Running Accuracy]: 0.7880,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 783:  52%|██████▎     | 783/1495 [04:51<04:02,  2.94it/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>Is the image of high quality?\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 text on the door clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the text on the door clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the text on the door clear in this 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]: 0.7880,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 783:  52%|██████▎     | 784/1495 [04:52<03:59,  2.97it/s]
[Running Accuracy]: 0.7870,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 784:  52%|██████▎     | 784/1495 [04:52<03:59,  2.97it/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>Is the text on the door 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 rich in color?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image rich in color?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image rich in color?\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]: 0.7870,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 784:  53%|██████▎     | 785/1495 [04:52<03:53,  3.04it/s]
[Running Accuracy]: 0.7873,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 785:  53%|█████▊     | 785/1495 [04:52<03:53,  3.04it/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>Is this image rich in color?\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 issues are present in the image?
A. Out of focus
B. Distortion
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following issues are present in the image?
A. Out of focus
B. Distortion
C. Underexposure
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following issues are present in the image?\nA. Out of focus\nB. Distortion\nC. Underexposure\nD. 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]: 0.7873,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 785:  53%|█████▊     | 786/1495 [04:52<03:48,  3.10it/s]
[Running Accuracy]: 0.7875,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 786:  53%|▌| 786/1495 [04:52<03:48,  3.10it/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>Which of the following issues are present in the image?\nA. Out of focus\nB. Distortion\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 the bridge in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bridge in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bridge 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]: 0.7875,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 786:  53%|▌| 787/1495 [04:53<03:49,  3.09it/s]
[Running Accuracy]: 0.7878,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 787:  53%|█████▊     | 787/1495 [04:53<03:49,  3.09it/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>Is the bridge 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>From which direction does the light come in the image?
A. Bottom
B. Right
C. Left
D. Top
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light come in the image?
A. Bottom
B. Right
C. Left
D. Top
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light come in the image?\nA. Bottom\nB. Right\nC. Left\nD. Top\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]: 0.7878,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 787:  53%|█████▊     | 788/1495 [04:53<03:47,  3.10it/s]
[Running Accuracy]: 0.7868,[Response]: D.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 788:  53%|████▋    | 788/1495 [04:53<03:47,  3.10it/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>From which direction does the light come in the image?\nA. Bottom\nB. Right\nC. Left\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>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([-31.5312], 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]: 0.7868,[Response]: D.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 788:  53%|████▋    | 789/1495 [04:53<04:04,  2.89it/s]
[Running Accuracy]: 0.7871,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 789:  53%|████▏   | 789/1495 [04:53<04:04,  2.89it/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 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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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?
A. Brightful
B. Medium
C. Gloomy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the image?
A. Brightful
B. Medium
C. Gloomy
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the image?\nA. Brightful\nB. Medium\nC. Gloomy\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]: 0.7871,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 789:  53%|████▏   | 790/1495 [04:54<03:56,  2.98it/s]
[Running Accuracy]: 0.7873,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 790:  53%|████▏   | 790/1495 [04:54<03:56,  2.98it/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 lighting condition of the image?\nA. Brightful\nB. Medium\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>Is this image motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image motion-blurred?\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]: 0.7873,[Response]: C.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 790:  53%|████▏   | 791/1495 [04:54<04:56,  2.37it/s]
[Running Accuracy]: 0.7876,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 791:  53%|█████▊     | 791/1495 [04:54<04:56,  2.37it/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>Is this image motion-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>How blurry is this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is this picture?
A. Mild
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is this picture?\nA. Mild\nB. Severe\nC. Moderate\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]: 0.7876,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 791:  53%|█████▊     | 792/1495 [04:54<04:31,  2.59it/s]
[Running Accuracy]: 0.7879,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 792:  53%|████▏   | 792/1495 [04:54<04:31,  2.59it/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 blurry is this picture?\nA. Mild\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>Which object in the image has severe motion blur?
A. Car
B. Building
C. Pedestrian
D. Street light
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image has severe motion blur?
A. Car
B. Building
C. Pedestrian
D. Street light
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image has severe motion blur?\nA. Car\nB. Building\nC. Pedestrian\nD. Street light\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]: 0.7879,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 792:  53%|████▏   | 793/1495 [04:55<04:09,  2.81it/s]
[Running Accuracy]: 0.7881,[Response]: A.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 793:  53%|█████▊     | 793/1495 [04:55<04:09,  2.81it/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>Which object in the image has severe motion blur?\nA. Car\nB. Building\nC. Pedestrian\nD. Street light\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise?\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])
 B.

[Running Accuracy]: 0.7881,[Response]: A.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 793:  53%|█████▊     | 794/1495 [04:55<04:04,  2.87it/s]
[Running Accuracy]: 0.7884,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 794:  53%|█████▊     | 794/1495 [04:55<04:04,  2.87it/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>Does this picture 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>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([-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]: 0.7884,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 794:  53%|█████▊     | 795/1495 [04:55<03:58,  2.93it/s]
[Running Accuracy]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 795:  53%|█████▎    | 795/1495 [04:55<03:58,  2.93it/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 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>Does this image look photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic?\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]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 795:  53%|█████▎    | 796/1495 [04:56<03:53,  2.99it/s]
[Running Accuracy]: 0.7889,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 796:  53%|██████▍     | 796/1495 [04:56<03:53,  2.99it/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>Does this image look photo-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 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([-31.3906], 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]: 0.7889,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 796:  53%|██████▍     | 797/1495 [04:56<03:54,  2.98it/s]
[Running Accuracy]: 0.7880,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 797:  53%|██████▍     | 797/1495 [04:56<03:54,  2.98it/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>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>What is the most prominent color in the image?
A. Red
B. Yellow
C. Black
D. Pink
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. Black
D. Pink
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. Black\nD. Pink\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]: 0.7880,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 797:  53%|██████▍     | 798/1495 [04:56<03:52,  3.00it/s]
[Running Accuracy]: 0.7882,[Response]: D.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 798:  53%|█████▎    | 798/1495 [04:56<03:52,  3.00it/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>What is the most prominent color in the image?\nA. Red\nB. Yellow\nC. Black\nD. Pink\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 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([-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]: 0.7882,[Response]: D.<|endoftext|>, [Correct Ans]: Pink, , [Prog]: 798:  53%|█████▎    | 799/1495 [04:57<03:47,  3.06it/s]
[Running Accuracy]: 0.7885,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 799:  53%|█████▎    | 799/1495 [04:57<03:47,  3.06it/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 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 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([-31.2188], 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]: 0.7885,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 799:  54%|█████▎    | 800/1495 [04:57<03:44,  3.09it/s]
[Running Accuracy]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 800:  54%|█████▉     | 800/1495 [04:57<03:44,  3.09it/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>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 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([-30.8750], 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]: 0.7887,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 800:  54%|█████▉     | 801/1495 [04:57<03:41,  3.13it/s]
[Running Accuracy]: 0.7890,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 801:  54%|██████▍     | 801/1495 [04:57<03:41,  3.13it/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>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>Does this image give a bright 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 bright visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a bright visual impression?\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]: 0.7890,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 801:  54%|██████▍     | 802/1495 [04:58<03:52,  2.97it/s]
[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 802:  54%|██████▍     | 802/1495 [04:58<03:52,  2.97it/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>Does this image give a bright visual impression?\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 experience does the image bring?
A. Frenzied
B. Dull
C. Fresh
D. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual experience does the image bring?
A. Frenzied
B. Dull
C. Fresh
D. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual experience does the image bring?\nA. Frenzied\nB. Dull\nC. Fresh\nD. Dark\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]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 802:  54%|██████▍     | 803/1495 [04:58<03:48,  3.03it/s]
[Running Accuracy]: 0.7883,[Response]: B.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 803:  54%|████▊    | 803/1495 [04:58<03:48,  3.03it/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>What kind of visual experience does the image bring?\nA. Frenzied\nB. Dull\nC. Fresh\nD. 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 this image with motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image with motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image with motion blur?\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]: 0.7883,[Response]: B.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 803:  54%|████▊    | 804/1495 [04:58<03:48,  3.02it/s]
[Running Accuracy]: 0.7886,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 804:  54%|██████▍     | 804/1495 [04:58<03:48,  3.02it/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>Is this image with motion blur?\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>From which direction does the light in the image come from?
A. Bottom left
B. Top left
C. Top right
D. Bottom right
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. Bottom left
B. Top left
C. Top right
D. Bottom right
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light in the image come from?\nA. Bottom left\nB. Top left\nC. Top right\nD. Bottom right\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]: 0.7886,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 804:  54%|██████▍     | 805/1495 [04:59<03:49,  3.01it/s]
[Running Accuracy]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Top left, , [Prog]: 805:  54%|███▏  | 805/1495 [04:59<03:49,  3.01it/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>From which direction does the light in the image come from?\nA. Bottom left\nB. Top left\nC. Top right\nD. Bottom right\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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. The moonlight
B. The sunlight
C. The streetlight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which is the main lighting source of this image?
A. The moonlight
B. The sunlight
C. The streetlight
Answer with the option's letter from the given choices directly.

prompts: [["Which is the main lighting source of this image?\nA. The moonlight\nB. The sunlight\nC. The streetlight\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]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Top left, , [Prog]: 805:  54%|███▏  | 806/1495 [04:59<04:45,  2.41it/s]
[Running Accuracy]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: The streetlight, , [Prog]: 806:  54%|▌| 806/1495 [04:59<04:45,  2.41it/
 {'prompt': "A chat between 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. The moonlight\nB. The sunlight\nC. The streetlight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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([-31.2031], 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]: 0.7891,[Response]: C.<|endoftext|>, [Correct Ans]: The streetlight, , [Prog]: 806:  54%|▌| 807/1495 [05:00<04:30,  2.54it/
[Running Accuracy]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 807:  54%|████▎   | 807/1495 [05:00<04:30,  2.54it/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 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>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([-30.8281], 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]: 0.7881,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 807:  54%|████▎   | 808/1495 [05:00<04:15,  2.69it/s]
[Running Accuracy]: 0.7884,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 808:  54%|██████▍     | 808/1495 [05:00<04:15,  2.69it/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>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>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([-31.2031], 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]: 0.7884,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 808:  54%|██████▍     | 809/1495 [05:00<04:06,  2.78it/s]
[Running Accuracy]: 0.7886,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 809:  54%|█████▉     | 809/1495 [05:00<04:06,  2.78it/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>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>What is the main distortion of the traffic light 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 main distortion of the traffic light 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 main distortion of the traffic light in this image?\nA. Noise\nB. Blur\nC. Over-exposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], 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]: 0.7886,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 809:  54%|█████▉     | 810/1495 [05:01<03:58,  2.88it/s]
[Running Accuracy]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 810:  54%|████▉    | 810/1495 [05:01<03:58,  2.88it/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>What is the main distortion of the traffic light 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>How blurry is this picture?
A. Severe
B. Mild
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is this picture?
A. Severe
B. Mild
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is this picture?\nA. Severe\nB. Mild\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]: 0.7889,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 810:  54%|████▉    | 811/1495 [05:01<03:51,  2.96it/s]
[Running Accuracy]: 0.7891,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 811:  54%|████▎   | 811/1495 [05:01<03:51,  2.96it/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 blurry is this picture?\nA. Severe\nB. Mild\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 waterfall in the image?
A. Very blurry
B. Somewhat blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the waterfall in the image?
A. Very blurry
B. Somewhat blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the waterfall in the image?\nA. Very blurry\nB. Somewhat blurry\nC. Not blurry 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])
 B.

[Running Accuracy]: 0.7891,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 811:  54%|████▎   | 812/1495 [05:01<03:47,  3.01it/s]
[Running Accuracy]: 0.7894,[Response]: B.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 812:  54%|▌| 812/1495 [05:01<03:47,  3.01it/
 {'prompt': "A chat between 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 waterfall in the image?\nA. Very blurry\nB. Somewhat 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>Are the two girls in the front of this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the two girls in the front of this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the two girls in the front of 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]: 0.7894,[Response]: B.<|endoftext|>, [Correct Ans]: Somewhat blurry, , [Prog]: 812:  54%|▌| 813/1495 [05:02<03:46,  3.01it/
[Running Accuracy]: 0.7897,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 813:  54%|█████▉     | 813/1495 [05:02<03:46,  3.01it/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>Are the two girls in the front of 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 the truck clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the truck clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the truck 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])
 B.

[Running Accuracy]: 0.7897,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 813:  54%|█████▉     | 814/1495 [05:02<03:43,  3.05it/s]
[Running Accuracy]: 0.7899,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 814:  54%|██████▌     | 814/1495 [05:02<03:43,  3.05it/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>Is the truck 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 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([-30.7500], 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]: 0.7899,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 814:  55%|██████▌     | 815/1495 [05:02<03:47,  2.99it/s]
[Running Accuracy]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 815:  55%|█████▉     | 815/1495 [05:02<03:47,  2.99it/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>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 there any presence of noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any presence of noise in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any presence of noise in the image?\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]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 815:  55%|██████     | 816/1495 [05:03<04:40,  2.42it/s]
[Running Accuracy]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 816:  55%|██████     | 816/1495 [05:03<04:40,  2.42it/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>Is there any presence of 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>Does this image give you a fresh visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give you a fresh visual impression?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give you a fresh visual impression?\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]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 816:  55%|██████     | 817/1495 [05:03<04:19,  2.62it/s]
[Running Accuracy]: 0.7895,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 817:  55%|██████▌     | 817/1495 [05:03<04:19,  2.62it/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>Does this image give you a fresh 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>Is the food very dark in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the food very dark in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the food very dark in this image?\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]: 0.7895,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 817:  55%|██████▌     | 818/1495 [05:03<04:04,  2.76it/s]
[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 818:  55%|██████▌     | 818/1495 [05:03<04:04,  2.76it/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>Is the food very dark 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 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([-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]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 818:  55%|██████▌     | 819/1495 [05:04<04:02,  2.79it/s]
[Running Accuracy]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 819:  55%|██▏ | 819/1495 [05:04<04:02,  2.79it/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 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>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([-31.0625], 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]: 0.7900,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 819:  55%|██▏ | 820/1495 [05:04<03:54,  2.88it/s]
[Running Accuracy]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 820:  55%|██████     | 820/1495 [05:04<03:54,  2.88it/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>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 the overall lighting of the image sufficient?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the overall lighting of the image sufficient?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the overall lighting of the image sufficient?\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]: 0.7902,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 820:  55%|██████     | 821/1495 [05:05<03:53,  2.89it/s]
[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 821:  55%|██████▌     | 821/1495 [05:05<03:53,  2.89it/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>Is the overall lighting of the image sufficient?\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. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness 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])
 B.

[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 821:  55%|██████▌     | 822/1495 [05:05<03:51,  2.90it/s]
[Running Accuracy]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 822:  55%|█████▍    | 822/1495 [05:05<03:51,  2.90it/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 brightness of the 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 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([-30.6562], 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]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 822:  55%|█████▌    | 823/1495 [05:05<03:50,  2.91it/s]
[Running Accuracy]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 823:  55%|██████     | 823/1495 [05:05<03:50,  2.91it/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>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>How is the color saturation of the sky 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 sky 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 sky 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]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 823:  55%|██████     | 824/1495 [05:06<03:48,  2.94it/s]
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 824:  55%|█████▌    | 824/1495 [05:06<03:48,  2.94it/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 color saturation of the sky 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>Which object is the focus in the image?
A. Large statue
B. Small statue
C. Car
D. Man wearing a hat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in the image?
A. Large statue
B. Small statue
C. Car
D. Man wearing a hat
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in the image?\nA. Large statue\nB. Small statue\nC. Car\nD. Man wearing a hat\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]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 824:  55%|█████▌    | 825/1495 [05:06<03:48,  2.93it/s]
[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Man wearing a hat, , [Prog]: 825:  55%|▌| 825/1495 [05:06<03:48,  2.93i
 {'prompt': "A chat between 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 the image?\nA. Large statue\nB. Small statue\nC. Car\nD. Man wearing a hat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Brown
B. Green
C. Yellow
D. Red
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most prominent color in the image?
A. Brown
B. Green
C. Yellow
D. Red
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Brown\nB. Green\nC. Yellow\nD. Red\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])
 D.

[Running Accuracy]: 0.7903,[Response]: B.<|endoftext|>, [Correct Ans]: Man wearing a hat, , [Prog]: 825:  55%|▌| 826/1495 [05:06<03:46,  2.95i
[Running Accuracy]: 0.7906,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 826:  55%|██████     | 826/1495 [05:06<03:46,  2.95it/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>What is the most prominent color in the image?\nA. Brown\nB. Green\nC. Yellow\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>Name the major distortion in this image.
A. Underexposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Name the major distortion in this image.
A. Underexposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Name the major distortion in this image.\nA. Underexposure\nB. Blur\nC. 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])
 B.

[Running Accuracy]: 0.7906,[Response]: D.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 826:  55%|██████     | 827/1495 [05:07<05:31,  2.01it/s]
[Running Accuracy]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 827:  55%|█████▌    | 827/1495 [05:07<05:31,  2.01it/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>Name the major distortion in this image.\nA. Underexposure\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>Was shallow depth of field effect 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 effect 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 effect used 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])
 B.

[Running Accuracy]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 827:  55%|█████▌    | 828/1495 [05:07<04:54,  2.26it/s]
[Running Accuracy]: 0.7899,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 828:  55%|██████▋     | 828/1495 [05:07<04:54,  2.26it/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>Was shallow depth of field effect 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>Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\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]: 0.7899,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 828:  55%|██████▋     | 829/1495 [05:08<04:21,  2.54it/s]
[Running Accuracy]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 829:  55%|██████▋     | 829/1495 [05:08<04:21,  2.54it/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>Does this picture have underexposure 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 puppy the focal point in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the puppy the focal point in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the puppy the focal point in this image?\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]: 0.7901,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 829:  56%|██████▋     | 830/1495 [05:08<04:12,  2.63it/s]
[Running Accuracy]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 830:  56%|██████     | 830/1495 [05:08<04:12,  2.63it/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>Is the puppy the focal point 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 large characters over-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the large characters over-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the large characters over-exposed?\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]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 830:  56%|██████     | 831/1495 [05:09<05:47,  1.91it/s]
[Running Accuracy]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 831:  56%|██████     | 831/1495 [05:09<05:47,  1.91it/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>Are the large characters over-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>How is the lighting condition of the man's face?
A. Bright
B. Dark
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting condition of the man's face?
A. Bright
B. Dark
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the man's face?\nA. Bright\nB. Dark\nC. Average\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]: 0.7906,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 831:  56%|██████     | 832/1495 [05:09<05:06,  2.16it/s]
[Running Accuracy]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 832:  56%|█████▌    | 832/1495 [05:09<05:06,  2.16it/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 lighting condition of the man's face?\nA. Bright\nB. Dark\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 bird feather texture very clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bird feather texture very clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bird feather texture very clear?\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])
 A.

[Running Accuracy]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 832:  56%|█████▌    | 833/1495 [05:10<04:44,  2.33it/s]
[Running Accuracy]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 833:  56%|██████▋     | 833/1495 [05:10<04:44,  2.33it/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>Is the bird feather texture 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>Which object in the picture is the focus?
A. Trees
B. Rock
C. Creek
D. Grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the picture is the focus?
A. Trees
B. Rock
C. Creek
D. Grass
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the picture is the focus?\nA. Trees\nB. Rock\nC. Creek\nD. Grass\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]: 0.7911,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 833:  56%|██████▋     | 834/1495 [05:10<04:27,  2.47it/s]
[Running Accuracy]: 0.7914,[Response]: C.<|endoftext|>, [Correct Ans]: Creek, , [Prog]: 834:  56%|█████    | 834/1495 [05:10<04:27,  2.47it/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>Which object in the picture is the focus?\nA. Trees\nB. Rock\nC. Creek\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 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([-30.8125], 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]: 0.7914,[Response]: C.<|endoftext|>, [Correct Ans]: Creek, , [Prog]: 834:  56%|█████    | 835/1495 [05:10<04:12,  2.61it/s]
[Running Accuracy]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 835:  56%|██████▏    | 835/1495 [05:10<04:12,  2.61it/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>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 is emphasized in the composition of this image?
A. The thatched cottage
B. The pine tree
C. The sitting man
D. The standing 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. The thatched cottage
B. The pine tree
C. The sitting man
D. The standing man
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of this image?\nA. The thatched cottage\nB. The pine tree\nC. The sitting man\nD. The standing man\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]: 0.7916,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 835:  56%|██████▏    | 836/1495 [05:11<04:02,  2.72it/s]
[Running Accuracy]: 0.7919,[Response]: D.<|endoftext|>, [Correct Ans]: The standing man, , [Prog]: 836:  56%|▌| 836/1495 [05:11<04:02,  2.72it
 {'prompt': "A chat between 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 thatched cottage\nB. The pine tree\nC. The sitting man\nD. The standing 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>How blurry is 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 is 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 is 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([-31.2188], 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]: 0.7919,[Response]: D.<|endoftext|>, [Correct Ans]: The standing man, , [Prog]: 836:  56%|▌| 837/1495 [05:11<03:50,  2.85it
[Running Accuracy]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 837:  56%|█▋ | 837/1495 [05:11<03:50,  2.85it/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 blurry is 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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 bridge in this 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 bridge in this 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 bridge in this image?\nA. Good\nB. Average\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])
 A.

[Running Accuracy]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 837:  56%|█▋ | 838/1495 [05:11<03:44,  2.93it/s]
[Running Accuracy]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 838:  56%|█████▌    | 838/1495 [05:11<03:44,  2.93it/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 color saturation of the bridge in this 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 the woman's lip?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the woman's lip?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the woman's lip?\nA. Acceptable\nB. Excellent\nC. Bad\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]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 838:  56%|█████▌    | 839/1495 [05:12<03:40,  2.97it/s]
[Running Accuracy]: 0.7914,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 839:  56%|██▏ | 839/1495 [05:12<03:40,  2.97it/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 sharpness of the woman's lip?\nA. Acceptable\nB. Excellent\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 part of the image is the focal point?
A. The ground
B. The black door frame
C. The white ceramic tiles
D. The man
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the focal point?
A. The ground
B. The black door frame
C. The white ceramic tiles
D. The man
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the focal point?\nA. The ground\nB. The black door frame\nC. The white ceramic tiles\nD. The man\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])
 D.

[Running Accuracy]: 0.7914,[Response]: A.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 839:  56%|██▏ | 840/1495 [05:12<03:37,  3.02it/s]
[Running Accuracy]: 0.7917,[Response]: D.<|endoftext|>, [Correct Ans]: The man, , [Prog]: 840:  56%|███▉   | 840/1495 [05:12<03:37,  3.02it/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>Which part of the image is the focal point?\nA. The ground\nB. The black door frame\nC. The white ceramic tiles\nD. The 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>Are the human faces clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the human faces clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the human faces clear in this image?\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]: 0.7917,[Response]: D.<|endoftext|>, [Correct Ans]: The man, , [Prog]: 840:  56%|███▉   | 841/1495 [05:12<03:36,  3.02it/s]
[Running Accuracy]: 0.7919,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 841:  56%|██████▊     | 841/1495 [05:12<03:36,  3.02it/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>Are the human faces 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>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([-31.1875], 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]: 0.7919,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 841:  56%|██████▊     | 842/1495 [05:12<03:36,  3.01it/s]
[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 842:  56%|██████▏    | 842/1495 [05:12<03:36,  3.01it/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 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 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([-31.1875], 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]: Low, , [Prog]: 842:  56%|██████▏    | 843/1495 [05:13<03:34,  3.04it/s]
[Running Accuracy]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 843:  56%|██████▏    | 843/1495 [05:13<03:34,  3.04it/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>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>What is the major distortion of the human riding on a horse in the middle 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 major distortion of the human riding on a horse in the middle 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 major distortion of the human riding on a horse in the middle 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([-31.2344], 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]: 0.7912,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 843:  56%|██████▏    | 844/1495 [05:13<04:08,  2.62it/s]
[Running Accuracy]: 0.7903,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 844:  56%|▌| 844/1495 [05:13<04:08,  2.62it/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>What is the major distortion of the human riding on a horse in the middle 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': 'C.<|endoftext|>'} 

prompt A chat between 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([-31.1406], 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]: 0.7903,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 844:  57%|▌| 845/1495 [05:14<04:05,  2.65it/s
[Running Accuracy]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 845:  57%|██████▏    | 845/1495 [05:14<04:05,  2.65it/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>Is this picture 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>Which object is in focus in this image?
A. The cake in front
B. The wine glass
C. The cake in back
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is in focus in this image?
A. The cake in front
B. The wine glass
C. The cake in back
Answer with the option's letter from the given choices directly.

prompts: [["Which object is in focus in this image?\nA. The cake in front\nB. The wine glass\nC. The cake in back\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]: 0.7905,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 845:  57%|██████▏    | 846/1495 [05:14<03:52,  2.80it/s]
[Running Accuracy]: 0.7908,[Response]: A.<|endoftext|>, [Correct Ans]: The cake in front, , [Prog]: 846:  57%|▌| 846/1495 [05:14<03:52,  2.80i
 {'prompt': "A chat between 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 in focus in this image?\nA. The cake in front\nB. The wine glass\nC. The cake in back\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 bananas in this image?
A. Noise
B. Low light
C. Over-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the bananas in this image?
A. Noise
B. Low light
C. Over-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the bananas in this image?\nA. Noise\nB. Low light\nC. Over-exposure\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]: 0.7908,[Response]: A.<|endoftext|>, [Correct Ans]: The cake in front, , [Prog]: 846:  57%|▌| 847/1495 [05:14<03:44,  2.89i
[Running Accuracy]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 847:  57%|█████    | 847/1495 [05:14<03:44,  2.89it/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>What is the main distortion of the bananas in this image?\nA. Noise\nB. Low light\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>Are the plants on top of the rock clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the plants on top of the rock clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the plants on top of the rock clear?\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]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 847:  57%|█████    | 848/1495 [05:15<04:33,  2.37it/s]
[Running Accuracy]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 848:  57%|██████▊     | 848/1495 [05:15<04:33,  2.37it/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>Are the plants on top of the rock 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 there an issue of 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 an issue of excessive noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an issue of excessive noise in the image?\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]: 0.7913,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 848:  57%|██████▊     | 849/1495 [05:15<04:14,  2.54it/s]
[Running Accuracy]: 0.7915,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 849:  57%|██████▊     | 849/1495 [05:15<04:14,  2.54it/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>Is there an issue of 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>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([-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]: 0.7915,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 849:  57%|██████▊     | 850/1495 [05:16<04:54,  2.19it/s]
[Running Accuracy]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 850:  57%|██████▊     | 850/1495 [05:16<04:54,  2.19it/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>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 saturation level of 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 level of the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["What is the saturation level of 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]: 0.7918,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 850:  57%|██████▊     | 851/1495 [05:16<04:19,  2.48it/s]
[Running Accuracy]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 851:  57%|█████▋    | 851/1495 [05:16<04:19,  2.48it/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>What is the saturation level 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>How is the overall brightness of this picture about the moon?
A. Low
B. High
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall brightness of this picture about the moon?
A. Low
B. High
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall brightness of this picture about the moon?\nA. Low\nB. High\nC. Average\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]: 0.7920,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 851:  57%|█████▋    | 852/1495 [05:16<04:07,  2.60it/s]
[Running Accuracy]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 852:  57%|██████▎    | 852/1495 [05:16<04:07,  2.60it/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 overall brightness of this picture about the moon?\nA. Low\nB. High\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 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([-30.7812], 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]: 0.7923,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 852:  57%|██████▎    | 853/1495 [05:17<03:55,  2.72it/s]
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 853:  57%|██████▎    | 853/1495 [05:17<03:55,  2.72it/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>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': 'A.<|endoftext|>'} 

prompt A chat 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 picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the trees in this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Do the trees in this picture have motion blur?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.5781], 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]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 853:  57%|██████▎    | 854/1495 [05:17<04:35,  2.33it/s]
[Running Accuracy]: 0.7916,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 854:  57%|██████▎    | 854/1495 [05:17<04:35,  2.33it/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>Do the trees 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 is the clarity 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 clarity of the image?
A. Poor
B. Good
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Poor\nB. Good\nC. Average\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]: 0.7916,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 854:  57%|██████▎    | 855/1495 [05:18<04:17,  2.49it/s]
[Running Accuracy]: 0.7906,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 855:  57%|████   | 855/1495 [05:18<04:17,  2.49it/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 clarity 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 color of the cloth held by the bullfighter in this 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 cloth held by the bullfighter in this image vivid?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the cloth held by the bullfighter in this image vivid?\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])
 A.

[Running Accuracy]: 0.7906,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 855:  57%|████   | 856/1495 [05:18<04:09,  2.56it/s]
[Running Accuracy]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 856:  57%|██████▎    | 856/1495 [05:18<04:09,  2.56it/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>Is the color of the cloth held by the bullfighter in this image vivid?\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 in this image?
A. Medium
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the contrast in this image?
A. Medium
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast in this image?\nA. Medium\nB. Strong\nC. Weak\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]: 0.7909,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 856:  57%|██████▎    | 857/1495 [05:19<04:47,  2.22it/s]
[Running Accuracy]: 0.7900,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 857:  57%|████▌   | 857/1495 [05:19<04:47,  2.22it/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 contrast in this image?\nA. Medium\nB. Strong\nC. Weak\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 wall?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the wall?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the wall?\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]: 0.7900,[Response]: C.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 857:  57%|████▌   | 858/1495 [05:19<04:22,  2.42it/s]
[Running Accuracy]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 858:  57%|█████▋    | 858/1495 [05:19<04:22,  2.42it/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 brightness of the wall?\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 the sky suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the sky suffer from over-exposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the sky suffer from over-exposure?\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]: 0.7902,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 858:  57%|█████▋    | 859/1495 [05:19<04:03,  2.61it/s]
[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 859:  57%|██████▎    | 859/1495 [05:19<04:03,  2.61it/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>Does the sky 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>What kind of visual feelings does the image give?
A. Fresh
B. Restless
C. Dark
D. Dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feelings does the image give?
A. Fresh
B. Restless
C. Dark
D. Dull
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feelings does the image give?\nA. Fresh\nB. Restless\nC. Dark\nD. Dull\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]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 859:  58%|██████▎    | 860/1495 [05:20<03:50,  2.76it/s]
[Running Accuracy]: 0.7907,[Response]: A.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 860:  58%|█████▏   | 860/1495 [05:20<03:50,  2.76it/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>What kind of visual feelings does the image give?\nA. Fresh\nB. Restless\nC. Dark\nD. 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>How is the color saturation of the sky 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 sky 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 sky in the image?\nA. Average\nB. Poor\nC. Good\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]: 0.7907,[Response]: A.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 860:  58%|█████▏   | 861/1495 [05:20<03:39,  2.89it/s]
[Running Accuracy]: 0.7909,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 861:  58%|█████▊    | 861/1495 [05:20<03:39,  2.89it/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 color saturation of the sky 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>How is the color saturation of the man's clothing 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 clothing 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 clothing in the image?\nA. Good\nB. Poor\nC. Average\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]: 0.7909,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 861:  58%|█████▊    | 862/1495 [05:20<03:36,  2.93it/s]
[Running Accuracy]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 862:  58%|█████▊    | 862/1495 [05:20<03:36,  2.93it/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 color saturation of the man's clothing 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>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([-31.3438], 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]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 862:  58%|█████▊    | 863/1495 [05:21<03:30,  3.01it/s]
[Running Accuracy]: 0.7914,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 863:  58%|█████▊    | 863/1495 [05:21<03:30,  3.01it/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 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 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([-31.2188], 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]: 0.7914,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 863:  58%|█████▊    | 864/1495 [05:21<03:34,  2.94it/s]
[Running Accuracy]: 0.7917,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 864:  58%|█▏| 864/1495 [05:21<03:34,  2.94it/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>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': 'A.<|endoftext|>'} 

prompt A chat between 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 character in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the character in the image?
A. Poor
B. Average
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the character in the image?\nA. Poor\nB. Average\nC. Good\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]: 0.7917,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 864:  58%|█▏| 865/1495 [05:21<03:26,  3.05it/s]
[Running Accuracy]: 0.7919,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 865:  58%|█████▊    | 865/1495 [05:21<03:26,  3.05it/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 clear is the character 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>Does the face textures of the penguin look real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the face textures of the penguin look real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the face textures of the penguin look real?\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]: 0.7919,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 865:  58%|█████▊    | 866/1495 [05:22<03:25,  3.06it/s]
[Running Accuracy]: 0.7921,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 866:  58%|██████▉     | 866/1495 [05:22<03:25,  3.06it/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>Does the face textures of the penguin look real?\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 not present in this image?
A. Underexposure
B. Out of Focus
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion is not present in this image?
A. Underexposure
B. Out of Focus
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion is not present in this image?\nA. Underexposure\nB. Out of Focus\nC. Overexposure\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]: 0.7921,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 866:  58%|██████▉     | 867/1495 [05:22<04:34,  2.29it/s]
[Running Accuracy]: 0.7924,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 867:  58%|▌| 867/1495 [05:22<04:34,  2.29it/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>Which distortion is not present in this image?\nA. Underexposure\nB. Out of Focus\nC. 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 character in 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 character in the image?
A. Moderate
B. Blurry
C. Clear
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the character in the image?\nA. Moderate\nB. Blurry\nC. Clear\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]: 0.7924,[Response]: A.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 867:  58%|▌| 868/1495 [05:23<04:13,  2.47it/s]
[Running Accuracy]: 0.7926,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 868:  58%|█████▏   | 868/1495 [05:23<04:13,  2.47it/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 clear is the character 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>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([-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]: 0.7926,[Response]: C.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 868:  58%|█████▏   | 869/1495 [05:23<03:56,  2.65it/s]
[Running Accuracy]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 869:  58%|██████▉     | 869/1495 [05:23<03:56,  2.65it/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>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>To what extent is the background water surface 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 water surface 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 water surface blurred in this image?\nA. Moderate\nB. Severe\nC. Slight\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2500], 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]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 869:  58%|██████▉     | 870/1495 [05:23<04:05,  2.54it/s]
[Running Accuracy]: 0.7920,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 870:  58%|████▋   | 870/1495 [05:23<04:05,  2.54it/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>To what extent is the background water surface 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>What is the major distortion of the vases 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 vases 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 vases in this image?\nA. Blur\nB. Noise\nC. Over-exposure\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]: 0.7920,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 870:  58%|████▋   | 871/1495 [05:24<03:49,  2.71it/s]
[Running Accuracy]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 871:  58%|█████▏   | 871/1495 [05:24<03:49,  2.71it/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>What is the major distortion of the vases 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>Is the saturation of the flowers higher than that of the butterflies in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the saturation of the flowers higher than that of the butterflies in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the saturation of the flowers higher than that of the butterflies 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]: 0.7922,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 871:  58%|█████▏   | 872/1495 [05:24<03:40,  2.83it/s]
[Running Accuracy]: 0.7924,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 872:  58%|██████▍    | 872/1495 [05:24<03:40,  2.83it/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>Is the saturation of the flowers higher than that of the butterflies 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 part of the image is the clearest?
A. Boat
B. Clouds
C. Field
D. Forest
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the clearest?
A. Boat
B. Clouds
C. Field
D. Forest
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the clearest?\nA. Boat\nB. Clouds\nC. Field\nD. Forest\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]: 0.7924,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 872:  58%|██████▍    | 873/1495 [05:24<03:31,  2.94it/s]
[Running Accuracy]: 0.7927,[Response]: A.<|endoftext|>, [Correct Ans]: Boat, , [Prog]: 873:  58%|█████▊    | 873/1495 [05:24<03:31,  2.94it/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>Which part of the image is the clearest?\nA. Boat\nB. Clouds\nC. Field\nD. Forest\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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 cup in this image vibrant?
A. Dim
B. Vibrant
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the cup in this image vibrant?
A. Dim
B. Vibrant
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the cup in this image vibrant?\nA. Dim\nB. Vibrant\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])
 B.

[Running Accuracy]: 0.7927,[Response]: A.<|endoftext|>, [Correct Ans]: Boat, , [Prog]: 873:  58%|█████▊    | 874/1495 [05:25<03:28,  2.98it/s]
[Running Accuracy]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 874:  58%|████   | 874/1495 [05:25<03:28,  2.98it/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>Is the color of the cup in this image vibrant?\nA. Dim\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>How is the clarity of the image's sky?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image's sky?
A. Blurry
B. Clear
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image's sky?\nA. Blurry\nB. Clear\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])
 B.

[Running Accuracy]: 0.7929,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 874:  59%|████   | 875/1495 [05:25<03:26,  3.00it/s]
[Running Accuracy]: 0.7931,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 875:  59%|█████▎   | 875/1495 [05:25<03:26,  3.00it/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 clarity of the image's sky?\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>What kind of visual perception does the content in the image give?
A. Lively
B. Dim
C. Intense
D. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the content in the image give?
A. Lively
B. Dim
C. Intense
D. Bright
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the content in the image give?\nA. Lively\nB. Dim\nC. Intense\nD. Bright\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]: 0.7931,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 875:  59%|█████▎   | 876/1495 [05:25<03:23,  3.04it/s]
[Running Accuracy]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 876:  59%|██████▍    | 876/1495 [05:25<03:23,  3.04it/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>What kind of visual perception does the content in the image give?\nA. Lively\nB. Dim\nC. Intense\nD. 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 part of this picture has overexposure issues?
A. Building
B. Trees
C. Grass
D. Sky
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this picture has overexposure issues?
A. Building
B. Trees
C. Grass
D. Sky
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this picture has overexposure issues?\nA. Building\nB. Trees\nC. Grass\nD. Sky\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]: 0.7922,[Response]: A.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 876:  59%|██████▍    | 877/1495 [05:26<04:07,  2.49it/s]
[Running Accuracy]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 877:  59%|██████▍    | 877/1495 [05:26<04:07,  2.49it/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>Which part of this picture has overexposure issues?\nA. Building\nB. Trees\nC. Grass\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 bright is this picture?
A. Bright
B. Normal
C. Dim
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How bright is this picture?
A. Bright
B. Normal
C. Dim
Answer with the option's letter from the given choices directly.

prompts: [["How bright is this picture?\nA. Bright\nB. Normal\nC. Dim\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]: 0.7913,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 877:  59%|██████▍    | 878/1495 [05:26<04:47,  2.15it/s]
[Running Accuracy]: 0.7916,[Response]: C.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 878:  59%|██████▍    | 878/1495 [05:26<04:47,  2.15it/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 bright is this picture?\nA. Bright\nB. Normal\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>Is the most vibrant object in the image a sofa?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the most vibrant object in the image a sofa?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the most vibrant object in the image a sofa?\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]: 0.7916,[Response]: C.<|endoftext|>, [Correct Ans]: Dim, , [Prog]: 878:  59%|██████▍    | 879/1495 [05:27<04:21,  2.36it/s]
[Running Accuracy]: 0.7907,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 879:  59%|███████     | 879/1495 [05:27<04:21,  2.36it/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>Is the most vibrant object in the image a sofa?\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 flowers in this photo vibrant?
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 photo vibrant?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the flowers in this photo vibrant?\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]: 0.7907,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 879:  59%|███████     | 880/1495 [05:27<04:07,  2.48it/s]
[Running Accuracy]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 880:  59%|██████▍    | 880/1495 [05:27<04:07,  2.48it/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>Is the color of the flowers in this photo 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 blurry are the people in the image?
A. Moderately 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 are the people in the image?
A. Moderately blurry
B. Very blurry
C. Not blurry at all
Answer with the option's letter from the given choices directly.

prompts: [["How blurry are the people in the image?\nA. Moderately blurry\nB. Very blurry\nC. Not blurry at all\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]: 0.7909,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 880:  59%|██████▍    | 881/1495 [05:27<03:50,  2.66it/s]
[Running Accuracy]: 0.7911,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 881:  59%|█▊ | 881/1495 [05:27<03:50,  2.66it/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 blurry are the people in the image?\nA. Moderately 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>What is the most severe image quality issue?
A. Distortion
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 the most severe image quality issue?
A. Distortion
B. Overexposure
C. Motion blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe image quality issue?\nA. Distortion\nB. Overexposure\nC. Motion blur\nD. Out of focus\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]: 0.7911,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 881:  59%|█▊ | 882/1495 [05:28<03:39,  2.79it/s]
[Running Accuracy]: 0.7914,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 882:  59%|█▏| 882/1495 [05:28<03:39,  2.79it/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>What is the most severe image quality issue?\nA. Distortion\nB. Overexposure\nC. Motion blur\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>Is the sky affected by over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the sky affected by over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the sky affected by over-exposure?\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. Yes

[Running Accuracy]: 0.7914,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 882:  59%|█▏| 883/1495 [05:28<03:41,  2.76it/s]
[Running Accuracy]: 0.7916,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 883:  59%|████▏  | 883/1495 [05:28<03:41,  2.76it/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>Is the sky affected by over-exposure?\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>Which part of the race car is over too bright?
A. The bottom part
B. The top part
C. The left part
D. The right part
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the race car is over too bright?
A. The bottom part
B. The top part
C. The left part
D. The right part
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the race car is over too bright?\nA. The bottom part\nB. The top part\nC. The left part\nD. The right part\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]: 0.7916,[Response]: A. Yes<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 883:  59%|████▏  | 884/1495 [05:29<04:06,  2.48it/s]
[Running Accuracy]: 0.7907,[Response]: B.<|endoftext|>, [Correct Ans]: The left part, , [Prog]: 884:  59%|▌| 884/1495 [05:29<04:06,  2.48it/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>Which part of the race car is over too bright?\nA. The bottom part\nB. The top part\nC. The left part\nD. The right 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>Which part of the image is in focus?
A. Ground
B. Buildings
C. Street lights
D. Cars
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is in focus?
A. Ground
B. Buildings
C. Street lights
D. Cars
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is in focus?\nA. Ground\nB. Buildings\nC. Street lights\nD. Cars\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]: 0.7907,[Response]: B.<|endoftext|>, [Correct Ans]: The left part, , [Prog]: 884:  59%|▌| 885/1495 [05:29<03:49,  2.66it/s]
[Running Accuracy]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Buildings, , [Prog]: 885:  59%|██▉  | 885/1495 [05:29<03:49,  2.66it/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>Which part of the image is in focus?\nA. Ground\nB. Buildings\nC. Street lights\nD. Cars\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 boat 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 boat 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 boat in the image?\nA. Poor\nB. Average\nC. Good\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]: 0.7910,[Response]: B.<|endoftext|>, [Correct Ans]: Buildings, , [Prog]: 885:  59%|██▉  | 886/1495 [05:29<03:38,  2.79it/s]
[Running Accuracy]: 0.7901,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 886:  59%|████▏  | 886/1495 [05:29<03:38,  2.79it/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 color saturation of the boat 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 the pet dog the focal point in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the pet dog the focal point in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the pet dog the focal point 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]: 0.7901,[Response]: C.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 886:  59%|████▏  | 887/1495 [05:30<03:30,  2.89it/s]
[Running Accuracy]: 0.7903,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 887:  59%|██████▌    | 887/1495 [05:30<03:30,  2.89it/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>Is the pet dog the focal point 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 photo clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this photo clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this photo 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])
 B.

[Running Accuracy]: 0.7903,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 887:  59%|██████▌    | 888/1495 [05:30<03:24,  2.96it/s]
[Running Accuracy]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 888:  59%|███████▏    | 888/1495 [05:30<03:24,  2.96it/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>Is this photo 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 color of the flowers in this image?
A. Monotonous
B. Medium
C. Vibrant
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. Monotonous
B. Medium
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the flowers in this image?\nA. Monotonous\nB. Medium\nC. Vibrant\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]: 0.7905,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 888:  59%|███████▏    | 889/1495 [05:30<03:20,  3.03it/s]
[Running Accuracy]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 889:  59%|████▊   | 889/1495 [05:30<03:20,  3.03it/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 color of the flowers in this image?\nA. Monotonous\nB. Medium\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject well-defined?\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]: 0.7908,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 889:  60%|████▊   | 890/1495 [05:30<03:16,  3.08it/s]
[Running Accuracy]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 890:  60%|██████▌    | 890/1495 [05:30<03:16,  3.08it/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>Is the main subject well-defined?\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 image composition, which object is emphasized in the center?
A. Flower
B. Stone
C. Dry grass
D. Red branch
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. Flower
B. Stone
C. Dry grass
D. Red branch
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. Flower\nB. Stone\nC. Dry grass\nD. Red branch\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]: 0.7910,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 890:  60%|██████▌    | 891/1495 [05:31<03:17,  3.06it/s]
[Running Accuracy]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Flower, , [Prog]: 891:  60%|████▊   | 891/1495 [05:31<03:17,  3.06it/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>In image composition, which object is emphasized in the center?\nA. Flower\nB. Stone\nC. Dry grass\nD. Red branch\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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. Underexosure
D. Overexposure
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. Underexosure
D. Overexposure
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. Underexosure\nD. Overexposure\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]: 0.7912,[Response]: A.<|endoftext|>, [Correct Ans]: Flower, , [Prog]: 891:  60%|████▊   | 892/1495 [05:31<04:12,  2.39it/s]
[Running Accuracy]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 892:  60%|█▊ | 892/1495 [05:31<04:12,  2.39it/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>What kind of distortion occurs in this image?\nA. Motion Blur\nB. Out of Focus\nC. Underexosure\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 sharpness of the cat's fur?
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 the cat's fur?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the cat's fur?\nA. Medium\nB. Low\nC. High\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]: 0.7904,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 892:  60%|█▊ | 893/1495 [05:32<03:57,  2.53it/s]
[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 893:  60%|█████▉    | 893/1495 [05:32<03:57,  2.53it/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 sharpness of the cat's fur?\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 severe noise is in this image?
A. Strong noise
B. Weak noise
C. No noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe noise is in this image?
A. Strong noise
B. Weak noise
C. No noise
Answer with the option's letter from the given choices directly.

prompts: [["How severe noise is in this image?\nA. Strong noise\nB. Weak noise\nC. No 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])
 B.

[Running Accuracy]: 0.7906,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 893:  60%|█████▉    | 894/1495 [05:32<04:37,  2.17it/s]
[Running Accuracy]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: No noise, , [Prog]: 894:  60%|███▌  | 894/1495 [05:32<04:37,  2.17it/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 severe noise is in this image?\nA. Strong noise\nB. Weak noise\nC. No 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 rich is the color of the image?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How rich is the color of the image?
A. Monotonous
B. Rich
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How rich is the color of the image?\nA. Monotonous\nB. Rich\nC. Moderate\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]: 0.7897,[Response]: B.<|endoftext|>, [Correct Ans]: No noise, , [Prog]: 894:  60%|███▌  | 895/1495 [05:33<04:09,  2.40it/s]
[Running Accuracy]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 895:  60%|██▍ | 895/1495 [05:33<04:09,  2.40it/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 rich is the color of the image?\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>Does this image give a bright 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 bright visual enjoyment?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a bright visual enjoyment?\nA. Yes\nB. No\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]: 0.7888,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 895:  60%|██▍ | 896/1495 [05:33<03:53,  2.57it/s]
[Running Accuracy]: 0.7891,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 896:  60%|██████▌    | 896/1495 [05:33<03:53,  2.57it/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>Does this image give a bright 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 this image both underexposed and motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image both underexposed and motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image both underexposed and motion-blurred?\nA. No\nB. Yes\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])
 B.

[Running Accuracy]: 0.7891,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 896:  60%|██████▌    | 897/1495 [05:34<04:46,  2.09it/s]
[Running Accuracy]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 897:  60%|██████▌    | 897/1495 [05:34<04:46,  2.09it/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>Is this image both underexposed and motion-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>How is the clarity 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 clarity of the image?
A. Fair
B. Bad
C. Excellent
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Fair\nB. Bad\nC. Excellent\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]: 0.7893,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 897:  60%|██████▌    | 898/1495 [05:34<04:16,  2.33it/s]
[Running Accuracy]: 0.7884,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 898:  60%|██████    | 898/1495 [05:34<04:16,  2.33it/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 clarity of the image?\nA. Fair\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 the image compressed and distorted?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image compressed and distorted?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image compressed and distorted?\nA. Yes\nB. No\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]: 0.7884,[Response]: C.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 898:  60%|██████    | 899/1495 [05:34<03:54,  2.54it/s]
[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 899:  60%|██████▌    | 899/1495 [05:34<03:54,  2.54it/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>Is the image compressed and distorted?\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 in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cat in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the cat in the image clear?\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])
 A.

[Running Accuracy]: 0.7875,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 899:  60%|██████▌    | 900/1495 [05:35<03:39,  2.71it/s]
[Running Accuracy]: 0.7878,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 900:  60%|███████▏    | 900/1495 [05:35<03:39,  2.71it/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>Is the cat 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>What is the worst distortion in this picture?
A. Out of focus
B. Overexposure
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. Out of focus
B. Overexposure
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. Out of focus\nB. Overexposure\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])
 A.

[Running Accuracy]: 0.7878,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 900:  60%|███████▏    | 901/1495 [05:35<03:29,  2.84it/s]
[Running Accuracy]: 0.7880,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 901:  60%|█▏| 901/1495 [05:35<03:29,  2.84it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Overexposure\nC. Underexposure\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>Which object in the image appears the brightest?
A. Wooden Door
B. Window
C. Pot
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image appears the brightest?
A. Wooden Door
B. Window
C. Pot
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image appears the brightest?\nA. Wooden Door\nB. Window\nC. Pot\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])
 B.

[Running Accuracy]: 0.7880,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 901:  60%|█▏| 902/1495 [05:35<03:26,  2.87it/s]
[Running Accuracy]: 0.7871,[Response]: B.<|endoftext|>, [Correct Ans]: Pot, , [Prog]: 902:  60%|██████▋    | 902/1495 [05:35<03:26,  2.87it/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>Which object in the image appears the brightest?\nA. Wooden Door\nB. Window\nC. Pot\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How colorful is this picture?
A. Colorful
B. Dull
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How colorful is this picture?\nA. Colorful\nB. Dull\nC. Fair\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]: 0.7871,[Response]: B.<|endoftext|>, [Correct Ans]: Pot, , [Prog]: 902:  60%|██████▋    | 903/1495 [05:36<04:06,  2.40it/s]
[Running Accuracy]: 0.7863,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 903:  60%|██████    | 903/1495 [05:36<04:06,  2.40it/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 colorful is this picture?\nA. Colorful\nB. Dull\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 clear is the person in the image?
A. Poor
B. Good
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the person in the image?
A. Poor
B. Good
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the person in the image?\nA. Poor\nB. Good\nC. Medium\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]: 0.7863,[Response]: B.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 903:  60%|██████    | 904/1495 [05:36<03:50,  2.56it/s]
[Running Accuracy]: 0.7854,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 904:  60%|████▊   | 904/1495 [05:36<03:50,  2.56it/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 clear is the person in the image?\nA. Poor\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>How is the overall 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 is the overall clarity 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 clarity of this image?\nA. Low\nB. Medium\nC. High\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]: 0.7854,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 904:  61%|████▊   | 905/1495 [05:37<03:35,  2.74it/s]
[Running Accuracy]: 0.7856,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 905:  61%|██████▋    | 905/1495 [05:37<03:35,  2.74it/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 overall 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>Is the composition of the image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of the image symmetrical?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of the image symmetrical?\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])
 A.

[Running Accuracy]: 0.7856,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 905:  61%|██████▋    | 906/1495 [05:37<03:27,  2.84it/s]
[Running Accuracy]: 0.7848,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 906:  61%|██████▋    | 906/1495 [05:37<03:27,  2.84it/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>Is the composition of the 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>Which part in this image is the clearest?
A. Big tree
B. Grassland
C. Woman
D. Man
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part in this image is the clearest?
A. Big tree
B. Grassland
C. Woman
D. Man
Answer with the option's letter from the given choices directly.

prompts: [["Which part in this image is the clearest?\nA. Big tree\nB. Grassland\nC. Woman\nD. Man\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]: 0.7848,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 906:  61%|██████▋    | 907/1495 [05:37<03:33,  2.76it/s]
[Running Accuracy]: 0.7839,[Response]: B.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 907:  61%|█████▍   | 907/1495 [05:37<03:33,  2.76it/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>Which part in this image is the clearest?\nA. Big tree\nB. Grassland\nC. Woman\nD. Man\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Average
B. Sunny
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. Average
B. Sunny
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. Average\nB. Sunny\nC. Gloomy\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]: 0.7839,[Response]: B.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 907:  61%|█████▍   | 908/1495 [05:38<03:32,  2.76it/s]
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 908:  61%|████▊   | 908/1495 [05:38<03:32,  2.76it/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 lighting condition of the background in this image?\nA. Average\nB. Sunny\nC. Gloomy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 main subject in the 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 condition of the main subject in the image?
A. Dark
B. Medium
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of the main subject in the image?\nA. Dark\nB. Medium\nC. 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])
 A.

[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 908:  61%|████▊   | 909/1495 [05:38<03:28,  2.81it/s]
[Running Accuracy]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 909:  61%|██████    | 909/1495 [05:38<03:28,  2.81it/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 lighting condition of the main subject in the 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>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([-31.3281], 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]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 909:  61%|██████    | 910/1495 [05:38<03:26,  2.84it/s]
[Running Accuracy]: 0.7835,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 910:  61%|████▊   | 910/1495 [05:38<03:26,  2.84it/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>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': 'A.<|endoftext|>'} 

prompt A chat between 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 black and white?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image black and white?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image black and white?\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]: 0.7835,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 910:  61%|████▊   | 911/1495 [05:39<03:16,  2.98it/s]
[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 911:  61%|██████▋    | 911/1495 [05:39<03:16,  2.98it/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>Is this image black and white?\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. White clouds
B. Sky
C. Green plants
D. Ground
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. White clouds
B. Sky
C. Green plants
D. Ground
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. White clouds\nB. Sky\nC. Green plants\nD. Ground\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]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 911:  61%|██████▋    | 912/1495 [05:39<03:16,  2.97it/s]
[Running Accuracy]: 0.7840,[Response]: C.<|endoftext|>, [Correct Ans]: Green plants, , [Prog]: 912:  61%|█▏| 912/1495 [05:39<03:16,  2.97it/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>Which object is the focus in this image?\nA. White clouds\nB. Sky\nC. Green plants\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>Is the cactus in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cactus in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cactus in this image clear?\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]: 0.7840,[Response]: C.<|endoftext|>, [Correct Ans]: Green plants, , [Prog]: 912:  61%|█▏| 913/1495 [05:39<03:14,  2.99it/s]
[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 913:  61%|██████▋    | 913/1495 [05:39<03:14,  2.99it/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>Is the cactus 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>What is the sharpest part of the image?
A. The upper body of the character
B. The lower body of the character
C. The flag
D. The sword
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest part of the image?
A. The upper body of the character
B. The lower body of the character
C. The flag
D. The sword
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest part of the image?\nA. The upper body of the character\nB. The lower body of the character\nC. The flag\nD. The sword\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]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 913:  61%|██████▋    | 914/1495 [05:40<03:12,  3.01it/s]
[Running Accuracy]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: The upper body of the character, , [Prog]: 914:  61%|▌| 914/1495 [05:40
 {'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 the sharpest part of the image?\nA. The upper body of the character\nB. The lower body of the character\nC. The flag\nD. The sword\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 issue does not exist in this picture?
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 kind of image quality issue does not exist in this picture?
A. Out of focus
B. Underexposure
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["Which kind of image quality issue does not exist in this picture?\nA. Out of focus\nB. Underexposure\nC. Overexposure\nD. Noise\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.7656], 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]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: The upper body of the character, , [Prog]: 914:  61%|▌| 915/1495 [05:40
[Running Accuracy]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 915:  61%|█▏| 915/1495 [05:40<03:14,  2.99it/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>Which kind of image quality issue does not exist in this picture?\nA. Out of focus\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>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([-31.0625], 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]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 915:  61%|█▏| 916/1495 [05:40<03:14,  2.98it/s]
[Running Accuracy]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 916:  61%|██████▋    | 916/1495 [05:40<03:14,  2.98it/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>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>Does this image give a vibrant 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 vibrant visual impression?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a vibrant visual impression?\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]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 916:  61%|██████▋    | 917/1495 [05:41<03:17,  2.92it/s]
[Running Accuracy]: 0.7819,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 917:  61%|██████▋    | 917/1495 [05:41<03:17,  2.92it/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>Does this image give a vibrant 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>How severe is the over-exposure problem in this image?
A. Not Severe
B. Very Severe
C. Somewhat Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the over-exposure problem in this image?
A. Not Severe
B. Very Severe
C. Somewhat Severe
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the over-exposure problem in this image?\nA. Not Severe\nB. Very Severe\nC. Somewhat Severe\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]: 0.7819,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 917:  61%|██████▊    | 918/1495 [05:41<03:57,  2.43it/s]
[Running Accuracy]: 0.7821,[Response]: B.<|endoftext|>, [Correct Ans]: Very Severe, , [Prog]: 918:  61%|█▊ | 918/1495 [05:41<03:57,  2.43it/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 severe is the over-exposure problem in this image?\nA. Not Severe\nB. Very Severe\nC. Somewhat Severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-30.6562], 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]: 0.7821,[Response]: B.<|endoftext|>, [Correct Ans]: Very Severe, , [Prog]: 918:  61%|█▊ | 919/1495 [05:41<03:39,  2.62it/s]
[Running Accuracy]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 919:  61%|███████▍    | 919/1495 [05:41<03:39,  2.62it/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>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>What kind of distortion most severely degrades the quality of the image?
A. Blur
B. Overexposure
C. Underexposure
D. Snow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion most severely degrades the quality of the image?
A. Blur
B. Overexposure
C. Underexposure
D. Snow
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion most severely degrades the quality of the image?\nA. Blur\nB. Overexposure\nC. Underexposure\nD. Snow\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])
 D.

[Running Accuracy]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 919:  62%|███████▍    | 920/1495 [05:42<03:26,  2.78it/s]
[Running Accuracy]: 0.7826,[Response]: D.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 920:  62%|██████▏   | 920/1495 [05:42<03:26,  2.78it/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>What kind of distortion most severely degrades the quality of the image?\nA. Blur\nB. Overexposure\nC. Underexposure\nD. Snow\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 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([-30.9062], 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]: 0.7826,[Response]: D.<|endoftext|>, [Correct Ans]: Snow, , [Prog]: 920:  62%|██████▏   | 921/1495 [05:42<04:10,  2.29it/s]
[Running Accuracy]: 0.7828,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 921:  62%|███████▍    | 921/1495 [05:42<04:10,  2.29it/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>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>Is the drink 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 drink in focus in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the drink in focus in this picture?\nA. No\nB. Yes\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]: 0.7828,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 921:  62%|███████▍    | 922/1495 [05:43<03:53,  2.46it/s]
[Running Accuracy]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 922:  62%|██████▊    | 922/1495 [05:43<03:53,  2.46it/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>Is the drink in focus in 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?
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([-30.8281], 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]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 922:  62%|██████▊    | 923/1495 [05:43<03:43,  2.56it/s]
[Running Accuracy]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 923:  62%|██████▊    | 923/1495 [05:43<03:43,  2.56it/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>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>Are the buildings in this image too bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the buildings in this image too bright?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the buildings in this image too bright?\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]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 923:  62%|██████▊    | 924/1495 [05:43<03:31,  2.70it/s]
[Running Accuracy]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 924:  62%|██████▊    | 924/1495 [05:43<03:31,  2.70it/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>Are the buildings in this image too 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 lighting of the guitar player in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the guitar player in this image?
A. Medium
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the guitar player in this image?\nA. Medium\nB. Dark\nC. Bright\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]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 924:  62%|██████▊    | 925/1495 [05:44<03:22,  2.82it/s]
[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 925:  62%|██████▏   | 925/1495 [05:44<03:22,  2.82it/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 lighting of the guitar player 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>What is the most severe distortion in this image?
A. Overexposure
B. Underexposure
C. Blurriness
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe distortion in this image?
A. Overexposure
B. Underexposure
C. Blurriness
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe distortion in this image?\nA. Overexposure\nB. Underexposure\nC. Blurriness\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])
 C.

[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 925:  62%|██████▏   | 926/1495 [05:44<04:01,  2.36it/s]
[Running Accuracy]: 0.7829,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 926:  62%|██▍ | 926/1495 [05:44<04:01,  2.36it/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>What is the most severe distortion in this image?\nA. Overexposure\nB. Underexposure\nC. Blurriness\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>Which distortion occurs in this image?
A. Compression Artifacts
B. Noise
C. Motion Blur
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion occurs in this image?
A. Compression Artifacts
B. Noise
C. Motion Blur
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion occurs in this image?\nA. Compression Artifacts\nB. Noise\nC. Motion Blur\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])
 D.

[Running Accuracy]: 0.7829,[Response]: C.<|endoftext|>, [Correct Ans]: Blurriness, , [Prog]: 926:  62%|██▍ | 927/1495 [05:45<03:39,  2.59it/s]
[Running Accuracy]: 0.7832,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 927:  62%|█▏| 927/1495 [05:45<03:39,  2.59it/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>Which distortion occurs in this image?\nA. Compression Artifacts\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>How is the overall 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 is the overall clarity of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall clarity of this image?\nA. Low\nB. High\nC. Medium\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]: 0.7832,[Response]: D.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 927:  62%|█▏| 928/1495 [05:45<03:25,  2.77it/s]
[Running Accuracy]: 0.7834,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 928:  62%|████▉   | 928/1495 [05:45<03:25,  2.77it/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 overall clarity 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>Is the text on the stone blurry in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the text on the stone blurry in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the text on the stone blurry 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])
 B.

[Running Accuracy]: 0.7834,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 928:  62%|████▉   | 929/1495 [05:45<03:16,  2.88it/s]
[Running Accuracy]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 929:  62%|███████▍    | 929/1495 [05:45<03:16,  2.88it/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>Is the text on the stone 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>To what extent is the tallest building in this image blurry?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the tallest building in this image blurry?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the tallest building in this image blurry?\nA. Severe\nB. Slight\nC. Moderate\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]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 929:  62%|███████▍    | 930/1495 [05:46<03:13,  2.92it/s]
[Running Accuracy]: 0.7839,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 930:  62%|████▉   | 930/1495 [05:46<03:13,  2.92it/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>To what extent is the tallest building in this image blurry?\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>Does this image come with vivid colors?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image come with vivid colors?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image come with vivid colors?\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]: 0.7839,[Response]: B.<|endoftext|>, [Correct Ans]: Slight, , [Prog]: 930:  62%|████▉   | 931/1495 [05:46<03:58,  2.36it/s]
[Running Accuracy]: 0.7841,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 931:  62%|███████▍    | 931/1495 [05:46<03:58,  2.36it/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>Does this image come with vivid colors?\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 moon 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 moon 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 moon in the image?\nA. Good\nB. Average\nC. Poor\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]: 0.7841,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 931:  62%|███████▍    | 932/1495 [05:47<03:41,  2.54it/s]
[Running Accuracy]: 0.7843,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 932:  62%|██████▏   | 932/1495 [05:47<03:41,  2.54it/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 color saturation of the moon 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>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([-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]: 0.7843,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 932:  62%|██████▏   | 933/1495 [05:47<03:54,  2.40it/s]
[Running Accuracy]: 0.7846,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 933:  62%|██████▊    | 933/1495 [05:47<03:54,  2.40it/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>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 there motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there motion blur in the image?\nA. Yes\nB. No\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.8281], 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]: 0.7846,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 933:  62%|██████▊    | 934/1495 [05:47<03:41,  2.54it/s]
[Running Accuracy]: 0.7848,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 934:  62%|███████▍    | 934/1495 [05:47<03:41,  2.54it/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>Is there motion blur 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 there any details in the sky of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any details in the sky of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is there any details in the sky of 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])
 A.

[Running Accuracy]: 0.7848,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 934:  63%|███████▌    | 935/1495 [05:48<04:07,  2.27it/s]
[Running Accuracy]: 0.7850,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 935:  63%|███████▌    | 935/1495 [05:48<04:07,  2.27it/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>Is there any details in the sky of 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>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([-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]: 0.7850,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 935:  63%|███████▌    | 936/1495 [05:48<03:45,  2.48it/s]
[Running Accuracy]: 0.7842,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 936:  63%|███████▌    | 936/1495 [05:48<03:45,  2.48it/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>Does this picture have overexposure 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>Is this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image colorful?\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]: 0.7842,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 936:  63%|███████▌    | 937/1495 [05:49<04:13,  2.20it/s]
[Running Accuracy]: 0.7844,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 937:  63%|███████▌    | 937/1495 [05:49<04:13,  2.20it/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>Is 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 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([-31.2500], 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]: 0.7844,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 937:  63%|███████▌    | 938/1495 [05:49<03:51,  2.41it/s]
[Running Accuracy]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 938:  63%|██████▉    | 938/1495 [05:49<03:51,  2.41it/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>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 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([-31.2188], 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]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 938:  63%|██████▉    | 939/1495 [05:49<03:36,  2.56it/s]
[Running Accuracy]: 0.7849,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 939:  63%|██████▉    | 939/1495 [05:49<03:36,  2.56it/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>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 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([-31.3438], 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]: 0.7849,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 939:  63%|██████▉    | 940/1495 [05:50<03:48,  2.43it/s]
[Running Accuracy]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 940:  63%|██████▉    | 940/1495 [05:50<03:48,  2.43it/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>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>What are the issues with the image?
A. Compression artifacts
B. Underexposure
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are the issues with the image?
A. Compression artifacts
B. Underexposure
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What are the issues with the image?\nA. Compression artifacts\nB. Underexposure\nC. Motion blur\nD. Overexposure\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]: 0.7851,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 940:  63%|██████▉    | 941/1495 [05:50<03:31,  2.61it/s]
[Running Accuracy]: 0.7843,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 941:  63%|█▎| 941/1495 [05:50<03:31,  2.61it/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>What are the issues with the image?\nA. Compression artifacts\nB. Underexposure\nC. Motion blur\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 the main color of petals in the image blue?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main color of petals in the image blue?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main color of petals in the image blue?\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]: 0.7843,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 941:  63%|█▎| 942/1495 [05:51<03:21,  2.75it/s]
[Running Accuracy]: 0.7845,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 942:  63%|███████▌    | 942/1495 [05:51<03:21,  2.75it/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>Is the main color of petals in the image blue?\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 ground suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the ground suffer from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the ground suffer from over-exposure?\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])
 A.

[Running Accuracy]: 0.7845,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 942:  63%|███████▌    | 943/1495 [05:51<03:43,  2.47it/s]
[Running Accuracy]: 0.7847,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 943:  63%|██████▉    | 943/1495 [05:51<03:43,  2.47it/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>Does the ground 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>What are the emotions conveyed by the image?
A. Pleasant
B. Calming
C. Terrifying
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are the emotions conveyed by the image?
A. Pleasant
B. Calming
C. Terrifying
Answer with the option's letter from the given choices directly.

prompts: [["What are the emotions conveyed by the image?\nA. Pleasant\nB. Calming\nC. Terrifying\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]: 0.7847,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 943:  63%|██████▉    | 944/1495 [05:51<03:27,  2.65it/s]
[Running Accuracy]: 0.7850,[Response]: C.<|endoftext|>, [Correct Ans]: Terrifying, , [Prog]: 944:  63%|██▌ | 944/1495 [05:51<03:27,  2.65it/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>What are the emotions conveyed by the image?\nA. Pleasant\nB. Calming\nC. Terrifying\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\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])
 C.

[Running Accuracy]: 0.7850,[Response]: C.<|endoftext|>, [Correct Ans]: Terrifying, , [Prog]: 944:  63%|██▌ | 945/1495 [05:52<03:22,  2.72it/s]
[Running Accuracy]: 0.7841,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 945:  63%|█████   | 945/1495 [05:52<03:22,  2.72it/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?\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 kind of blur exist in this image?
A. Glass blur
B. Defocus blur
C. Zoom blur
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of blur exist in this image?
A. Glass blur
B. Defocus blur
C. Zoom blur
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of blur exist in this image?\nA. Glass blur\nB. Defocus blur\nC. Zoom blur\nD. Motion blur\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]: 0.7841,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 945:  63%|█████   | 946/1495 [05:52<03:56,  2.33it/s]
[Running Accuracy]: 0.7844,[Response]: B.<|endoftext|>, [Correct Ans]: Defocus blur, , [Prog]: 946:  63%|█▎| 946/1495 [05:52<03:56,  2.33it/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>What kind of blur exist in this image?\nA. Glass blur\nB. Defocus blur\nC. Zoom blur\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 any details under the water still clearly visible?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is any details under the water still clearly visible?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is any details under the water still clearly visible?\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]: 0.7844,[Response]: B.<|endoftext|>, [Correct Ans]: Defocus blur, , [Prog]: 946:  63%|█▎| 947/1495 [05:53<03:37,  2.52it/s]
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 947:  63%|███████▌    | 947/1495 [05:53<03:37,  2.52it/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>Is any details under the water still clearly visible?\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 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([-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]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 947:  63%|███████▌    | 948/1495 [05:53<03:22,  2.70it/s]
[Running Accuracy]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 948:  63%|███████▌    | 948/1495 [05:53<03:22,  2.70it/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>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>How clear is the plant in the image?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the plant in the image?
A. Good
B. Bad
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the plant in the image?\nA. Good\nB. Bad\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])
 A.

[Running Accuracy]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 948:  63%|███████▌    | 949/1495 [05:54<04:19,  2.11it/s]
[Running Accuracy]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 949:  63%|██████▎   | 949/1495 [05:54<04:19,  2.11it/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 clear is the plant in the image?\nA. Good\nB. Bad\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>Is the down of the little duck in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the down of the little duck in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the down of the little duck in the image clear?\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]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 949:  64%|██████▎   | 950/1495 [05:54<03:56,  2.30it/s]
[Running Accuracy]: 0.7832,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 950:  64%|███████▋    | 950/1495 [05:54<03:56,  2.30it/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>Is the down of the little duck 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 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([-31.3750], 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]: 0.7832,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 950:  64%|███████▋    | 951/1495 [05:54<03:39,  2.47it/s]
[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 951:  64%|██████▉    | 951/1495 [05:54<03:39,  2.47it/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>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 degree of blurriness of 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
What is the degree of blurriness of 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: [["What is the degree of blurriness of 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([-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]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 951:  64%|███████    | 952/1495 [05:55<03:25,  2.64it/s]
[Running Accuracy]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 952:  64%|█▉ | 952/1495 [05:55<03:25,  2.64it/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>What is the degree of blurriness of 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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 object in the image?
A. The small grass in the middle
B. The tree hole
C. The leaf in the bottom right corner
D. The tree stump
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most blurry object in the image?
A. The small grass in the middle
B. The tree hole
C. The leaf in the bottom right corner
D. The tree stump
Answer with the option's letter from the given choices directly.

prompts: [["What is the most blurry object in the image?\nA. The small grass in the middle\nB. The tree hole\nC. The leaf in the bottom right corner\nD. The tree stump\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]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 952:  64%|█▉ | 953/1495 [05:55<03:21,  2.69it/s]
[Running Accuracy]: 0.7838,[Response]: C.<|endoftext|>, [Correct Ans]: The leaf in the bottom right corner, , [Prog]: 953:  64%|▋| 953/1495 [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 blurry object in the image?\nA. The small grass in the middle\nB. The tree hole\nC. The leaf in the bottom right corner\nD. The tree stump\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Poor
B. Fair
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Poor\nB. Fair\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])
 A.

[Running Accuracy]: 0.7838,[Response]: C.<|endoftext|>, [Correct Ans]: The leaf in the bottom right corner, , [Prog]: 953:  64%|▋| 954/1495 [0
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 954:  64%|██████▍   | 954/1495 [05:56<03:56,  2.29it/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 sharpness 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 focus correct in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus correct in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus correct in the image?\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]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 954:  64%|██████▍   | 955/1495 [05:56<03:40,  2.45it/s]
[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 955:  64%|███████    | 955/1495 [05:56<03:40,  2.45it/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>Is the focus correct 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>In the composition of the image, which object is emphasized in the center?
A. Plastic table and chairs
B. Table
C. Plants
D. Grass circle
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. Plastic table and chairs
B. Table
C. Plants
D. Grass circle
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. Plastic table and chairs\nB. Table\nC. Plants\nD. Grass circle\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])
 B.

[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 955:  64%|███████    | 956/1495 [05:56<03:25,  2.62it/s]
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Table, , [Prog]: 956:  64%|█████▊   | 956/1495 [05:56<03:25,  2.62it/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>In the composition of the image, which object is emphasized in the center?\nA. Plastic table and chairs\nB. Table\nC. Plants\nD. Grass circle\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.1406], 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]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Table, , [Prog]: 956:  64%|█████▊   | 957/1495 [05:57<03:24,  2.63it/s]
[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 957:  64%|███████▋    | 957/1495 [05:57<03:24,  2.63it/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>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 woman on the right side of the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman on the right side of the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman on the right side of the image clear?\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]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 957:  64%|███████▋    | 958/1495 [05:57<03:17,  2.72it/s]
[Running Accuracy]: 0.7829,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 958:  64%|███████    | 958/1495 [05:57<03:17,  2.72it/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>Is the woman on the right side 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>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([-30.5625], 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]: 0.7829,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 958:  64%|███████    | 959/1495 [05:57<03:07,  2.87it/s]
[Running Accuracy]: 0.7831,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 959:  64%|███████    | 959/1495 [05:57<03:07,  2.87it/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>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>What is not one of the quality issues of this picture?
A. Low clarity
B. Not clear
C. Low sharpness
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is not one of the quality issues of this picture?
A. Low clarity
B. Not clear
C. Low sharpness
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is not one of the quality issues of this picture?\nA. Low clarity\nB. Not clear\nC. Low sharpness\nD. Motion 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])
 A.

[Running Accuracy]: 0.7831,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 959:  64%|███████    | 960/1495 [05:58<02:59,  2.98it/s]
[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 960:  64%|█▉ | 960/1495 [05:58<02:59,  2.98it/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>What is not one of the quality issues of this picture?\nA. Low clarity\nB. Not clear\nC. Low sharpness\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 photography techniques were used in the image?
A. Motion blur
B. Strong contrast
C. Shallow depth of field
D. Black and white filter
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What photography techniques were used in the image?
A. Motion blur
B. Strong contrast
C. Shallow depth of field
D. Black and white filter
Answer with the option's letter from the given choices directly.

prompts: [["What photography techniques were used in the image?\nA. Motion blur\nB. Strong contrast\nC. Shallow depth of field\nD. Black and white filter\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]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 960:  64%|█▉ | 961/1495 [05:58<02:58,  2.99it/s]
[Running Accuracy]: 0.7825,[Response]: D.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 961:  64%|▋| 961/1495 [05:58<02:58,  
 {'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 photography techniques were used in the image?\nA. Motion blur\nB. Strong contrast\nC. Shallow depth of field\nD. Black and white filter\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 has the highest clarity?
A. Background
B. Hand
C. Facial features
D. Clothing
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image has the highest clarity?
A. Background
B. Hand
C. Facial features
D. Clothing
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image has the highest clarity?\nA. Background\nB. Hand\nC. Facial features\nD. Clothing\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]: 0.7825,[Response]: D.<|endoftext|>, [Correct Ans]: Black and white filter, , [Prog]: 961:  64%|▋| 962/1495 [05:58<02:54,  
[Running Accuracy]: 0.7827,[Response]: C.<|endoftext|>, [Correct Ans]: Facial features, , [Prog]: 962:  64%|▋| 962/1495 [05:58<02:54,  3.05it/
 {'prompt': "A chat between 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 highest clarity?\nA. Background\nB. Hand\nC. Facial features\nD. Clothing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 thing in the image?
A. Rider
B. Flower bed
C. Railing
D. Audience
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest thing in the image?
A. Rider
B. Flower bed
C. Railing
D. Audience
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest thing in the image?\nA. Rider\nB. Flower bed\nC. Railing\nD. Audience\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]: 0.7827,[Response]: C.<|endoftext|>, [Correct Ans]: Facial features, , [Prog]: 962:  64%|▋| 963/1495 [05:59<02:55,  3.04it/
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Rider, , [Prog]: 963:  64%|█████▊   | 963/1495 [05:59<02:55,  3.04it/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>What is the clearest thing in the image?\nA. Rider\nB. Flower bed\nC. Railing\nD. Audience\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 the image?
A. Galaxy
B. Sun
C. Cloud
D. Astronaut
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the darkest part of the image?
A. Galaxy
B. Sun
C. Cloud
D. Astronaut
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest part of the image?\nA. Galaxy\nB. Sun\nC. Cloud\nD. Astronaut\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])
 D.

[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Rider, , [Prog]: 963:  64%|█████▊   | 964/1495 [05:59<02:58,  2.98it/s]
[Running Accuracy]: 0.7832,[Response]: D.<|endoftext|>, [Correct Ans]: Astronaut, , [Prog]: 964:  64%|███▏ | 964/1495 [05:59<02:58,  2.98it/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>What is the darkest part of the image?\nA. Galaxy\nB. Sun\nC. Cloud\nD. Astronaut\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 a problem with 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 a problem with excessive noise in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there a problem with excessive noise in the image?\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]: 0.7832,[Response]: D.<|endoftext|>, [Correct Ans]: Astronaut, , [Prog]: 964:  65%|███▏ | 965/1495 [05:59<02:54,  3.03it/s]
[Running Accuracy]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 965:  65%|███████▋    | 965/1495 [05:59<02:54,  3.03it/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>Is there a problem with 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>Does this image give a refreshing feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a refreshing feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a refreshing feeling?\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]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 965:  65%|███████▊    | 966/1495 [05:59<02:52,  3.06it/s]
[Running Accuracy]: 0.7826,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 966:  65%|███████▊    | 966/1495 [05:59<02:52,  3.06it/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>Does this image give a refreshing 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>What is the main distortion of 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 main distortion of this image?
A. Over-exposure
B. Blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of this image?\nA. Over-exposure\nB. Blur\nC. 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]: 0.7826,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 966:  65%|███████▊    | 967/1495 [06:00<03:31,  2.50it/s]
[Running Accuracy]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 967:  65%|▋| 967/1495 [06:00<03:31,  2.50it/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>What is the main distortion of this image?\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>What's the worst distortion in this picture?
A. Motion blur
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. Motion blur
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. Motion blur\nB. Out of focus\nC. Noise\nD. Overexposure\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]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Over-exposure, , [Prog]: 967:  65%|▋| 968/1495 [06:01<03:44,  2.35it/s]
[Running Accuracy]: 0.7831,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 968:  65%|█▎| 968/1495 [06:01<03:44,  2.35it/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>What's the worst distortion in this picture?\nA. Motion blur\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 object in the center of focus in the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the object in the center of focus in the image composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the object in the center of focus in the image composition?\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]: 0.7831,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 968:  65%|█▎| 969/1495 [06:01<03:25,  2.56it/s]
[Running Accuracy]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 969:  65%|███████▏   | 969/1495 [06:01<03:25,  2.56it/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>Is the object in the center of focus 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>Which color is the most eye-catching in this image?
A. Brown
B. Yellow
C. Green
D. White
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. Brown
B. Yellow
C. Green
D. White
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the most eye-catching in this image?\nA. Brown\nB. Yellow\nC. Green\nD. White\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]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 969:  65%|███████▏   | 970/1495 [06:01<03:12,  2.73it/s]
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 970:  65%|█████▏  | 970/1495 [06:01<03:12,  2.73it/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>Which color is the most eye-catching in this image?\nA. Brown\nB. Yellow\nC. Green\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. 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([-30.9219], 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]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 970:  65%|█████▏  | 971/1495 [06:02<04:01,  2.17it/s]
[Running Accuracy]: 0.7837,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 971:  65%|███████▊    | 971/1495 [06:02<04:01,  2.17it/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>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 object in the image is relatively blurry?
A. Net curtain
B. Cushion
C. Kitten
D. Window
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is relatively blurry?
A. Net curtain
B. Cushion
C. Kitten
D. Window
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is relatively blurry?\nA. Net curtain\nB. Cushion\nC. Kitten\nD. Window\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]: 0.7837,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 971:  65%|███████▊    | 972/1495 [06:02<03:38,  2.39it/s]
[Running Accuracy]: 0.7829,[Response]: D.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 972:  65%|█████▏  | 972/1495 [06:02<03:38,  2.39it/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>Which object in the image is relatively blurry?\nA. Net curtain\nB. Cushion\nC. Kitten\nD. Window\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 emphasized in the center in the composition of the image?
A. Chair
B. Tree
C. Grass
D. Person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center in the composition of the image?
A. Chair
B. Tree
C. Grass
D. Person
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center in the composition of the image?\nA. Chair\nB. Tree\nC. Grass\nD. Person\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])
 D.

[Running Accuracy]: 0.7829,[Response]: D.<|endoftext|>, [Correct Ans]: Kitten, , [Prog]: 972:  65%|█████▏  | 973/1495 [06:02<03:22,  2.57it/s]
[Running Accuracy]: 0.7831,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 973:  65%|█████▏  | 973/1495 [06:02<03:22,  2.57it/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>Which object is emphasized in the center in the composition of the image?\nA. Chair\nB. Tree\nC. Grass\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>Are the lighting conditions for the ice cream in the image good?
A. Good
B. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the lighting conditions for the ice cream in the image good?
A. Good
B. Poor
Answer with the option's letter from the given choices directly.

prompts: [["Are the lighting conditions for the ice cream in the image good?\nA. Good\nB. 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]: 0.7831,[Response]: D.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 973:  65%|█████▏  | 974/1495 [06:03<03:10,  2.73it/s]
[Running Accuracy]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 974:  65%|██████▌   | 974/1495 [06:03<03:10,  2.73it/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>Are the lighting conditions for the ice cream in the image good?\nA. Good\nB. 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 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([-31.2344], 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]: 0.7834,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 974:  65%|██████▌   | 975/1495 [06:03<03:01,  2.86it/s]
[Running Accuracy]: 0.7836,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 975:  65%|██████▌   | 975/1495 [06:03<03:01,  2.86it/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 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 are some photography techniques to improve image quality?
A. Motion blur
B. High contrast
C. Shallow depth of field
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are some photography techniques to improve image quality?
A. Motion blur
B. High contrast
C. Shallow depth of field
Answer with the option's letter from the given choices directly.

prompts: [["What are some photography techniques to improve image quality?\nA. Motion blur\nB. High contrast\nC. Shallow depth of field\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]: 0.7836,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 975:  65%|██████▌   | 976/1495 [06:03<02:57,  2.92it/s]
[Running Accuracy]: 0.7838,[Response]: C.<|endoftext|>, [Correct Ans]: Shallow depth of field, , [Prog]: 976:  65%|▋| 976/1495 [06:03<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>What are some photography techniques to improve image quality?\nA. Motion blur\nB. High contrast\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 part of the image suffering from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is part of the image suffering from over-exposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is part of the image suffering from over-exposure?\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]: 0.7838,[Response]: C.<|endoftext|>, [Correct Ans]: Shallow depth of field, , [Prog]: 976:  65%|▋| 977/1495 [06:04<03:29,  
[Running Accuracy]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 977:  65%|███████▏   | 977/1495 [06:04<03:29,  2.47it/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>Is part of the image suffering 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>Does this image give you a fresh visual feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give you a fresh visual feeling?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give you a fresh visual feeling?\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]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 977:  65%|███████▏   | 978/1495 [06:04<03:19,  2.60it/s]
[Running Accuracy]: 0.7832,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 978:  65%|███████▊    | 978/1495 [06:04<03:19,  2.60it/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>Does this image give you a fresh visual 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>What is the most apparent distortion for the human just under the light?
A. Noise
B. Blur
C. Low contrast
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion for the human just under the light?
A. Noise
B. Blur
C. Low contrast
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion for the human just under the light?\nA. Noise\nB. Blur\nC. Low contrast\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]: 0.7832,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 978:  65%|███████▊    | 979/1495 [06:05<03:53,  2.21it/s]
[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 979:  65%|██████▌   | 979/1495 [06:05<03:53,  2.21it/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>What is the most apparent distortion for the human just under the light?\nA. Noise\nB. Blur\nC. Low contrast\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 are affected by the problem of underexposure in images?
A. Truck
B. Airplane
C. Palm tree
D. Car
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What objects are affected by the problem of underexposure in images?
A. Truck
B. Airplane
C. Palm tree
D. Car
Answer with the option's letter from the given choices directly.

prompts: [["What objects are affected by the problem of underexposure in images?\nA. Truck\nB. Airplane\nC. Palm tree\nD. Car\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]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 979:  66%|██████▌   | 980/1495 [06:05<03:36,  2.38it/s]
[Running Accuracy]: 0.7816,[Response]: B.<|endoftext|>, [Correct Ans]: Palm tree, , [Prog]: 980:  66%|███▎ | 980/1495 [06:05<03:36,  2.38it/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>What objects are affected by the problem of underexposure in images?\nA. Truck\nB. Airplane\nC. Palm tree\nD. 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>Which object in the image is the focus?
A. Crow
B. Ground
C. Tree trunk
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the focus?
A. Crow
B. Ground
C. Tree trunk
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the focus?\nA. Crow\nB. Ground\nC. Tree trunk\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]: 0.7816,[Response]: B.<|endoftext|>, [Correct Ans]: Palm tree, , [Prog]: 980:  66%|███▎ | 981/1495 [06:06<03:21,  2.56it/s]
[Running Accuracy]: 0.7819,[Response]: A.<|endoftext|>, [Correct Ans]: Crow, , [Prog]: 981:  66%|██████▌   | 981/1495 [06:06<03:21,  2.56it/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>Which object in the image is the focus?\nA. Crow\nB. Ground\nC. Tree trunk\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 with good details?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image clear with good details?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image clear with good details?\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]: 0.7819,[Response]: A.<|endoftext|>, [Correct Ans]: Crow, , [Prog]: 981:  66%|██████▌   | 982/1495 [06:06<03:09,  2.71it/s]
[Running Accuracy]: 0.7821,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 982:  66%|███████▉    | 982/1495 [06:06<03:09,  2.71it/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>Is this image clear with good details?\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 part in this image?
A. grilled cold noodles
B. tabletop
C. soy sauce
D. bowl
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the sharpest part in this image?
A. grilled cold noodles
B. tabletop
C. soy sauce
D. bowl
Answer with the option's letter from the given choices directly.

prompts: [["What is the sharpest part in this image?\nA. grilled cold noodles\nB. tabletop\nC. soy sauce\nD. bowl\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]: 0.7821,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 982:  66%|███████▉    | 983/1495 [06:06<03:00,  2.83it/s]
[Running Accuracy]: 0.7813,[Response]: D.<|endoftext|>, [Correct Ans]: grilled cold noodles, , [Prog]: 983:  66%|▋| 983/1495 [06:06<03:00,  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 sharpest part in this image?\nA. grilled cold noodles\nB. tabletop\nC. soy sauce\nD. bowl\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 underexposure issue 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 issue in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure issue 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])
 B.

[Running Accuracy]: 0.7813,[Response]: D.<|endoftext|>, [Correct Ans]: grilled cold noodles, , [Prog]: 983:  66%|▋| 984/1495 [06:07<02:59,  2.
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 984:  66%|███████▉    | 984/1495 [06:07<02:59,  2.85it/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>Is there an underexposure issue 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 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
How 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: [["How 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([-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]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 984:  66%|███████▉    | 985/1495 [06:07<03:02,  2.79it/s]
[Running Accuracy]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 985:  66%|███████▏   | 985/1495 [06:07<03:02,  2.79it/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 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 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([-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]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 985:  66%|███████▎   | 986/1495 [06:08<03:49,  2.22it/s]
[Running Accuracy]: 0.7809,[Response]: A.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 986:  66%|███▉  | 986/1495 [06:08<03:49,  2.22it/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 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': 'A.<|endoftext|>'} 

prompt A chat 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 in this image, which object is emphasized in the center of the image?
A. People
B. Building
C. Ground
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In the composition in this image, which object is emphasized in the center of the image?
A. People
B. Building
C. Ground
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["In the composition in this image, which object is emphasized in the center of the image?\nA. People\nB. Building\nC. Ground\nD. Trees\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]: 0.7809,[Response]: A.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 986:  66%|███▉  | 987/1495 [06:08<04:08,  2.04it/s]
[Running Accuracy]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: People, , [Prog]: 987:  66%|█████▎  | 987/1495 [06:08<04:08,  2.04it/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>In the composition in this image, which object is emphasized in the center of the image?\nA. People\nB. Building\nC. Ground\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>How is the color of the food in this dish?
A. Medium
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the food in this dish?
A. Medium
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the food in this dish?\nA. Medium\nB. Monotonous\nC. Vibrant\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]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: People, , [Prog]: 987:  66%|█████▎  | 988/1495 [06:09<03:44,  2.26it/s]
[Running Accuracy]: 0.7814,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 988:  66%|████▋  | 988/1495 [06:09<03:44,  2.26it/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 color of the food in this dish?\nA. Medium\nB. Monotonous\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["Is the people in this picture darker than the wall?\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]: 0.7814,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 988:  66%|████▋  | 989/1495 [06:09<03:25,  2.47it/s]
[Running Accuracy]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 989:  66%|███████▎   | 989/1495 [06:09<03:25,  2.47it/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>Is the people in this picture darker than the wall?\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. 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([-30.9219], 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]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 989:  66%|███████▎   | 990/1495 [06:09<03:13,  2.62it/s]
[Running Accuracy]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 990:  66%|██████▌   | 990/1495 [06:09<03:13,  2.62it/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 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>Which object in the image is heavily affected by motion blur?
A. The girl standing and playing basketball
B. The girl sitting down
C. The ground
D. The backpack
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is heavily affected by motion blur?
A. The girl standing and playing basketball
B. The girl sitting down
C. The ground
D. The backpack
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is heavily affected by motion blur?\nA. The girl standing and playing basketball\nB. The girl sitting down\nC. The ground\nD. The backpack\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]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 990:  66%|██████▋   | 991/1495 [06:09<03:02,  2.76it/s]
[Running Accuracy]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: The girl standing and playing basketball, , [Prog]: 991:  66%|▋| 991/14
 {'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 image is heavily affected by motion blur?\nA. The girl standing and playing basketball\nB. The girl sitting down\nC. The ground\nD. The backpack\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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([-30.4375], 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]: 0.7820,[Response]: A.<|endoftext|>, [Correct Ans]: The girl standing and playing basketball, , [Prog]: 991:  66%|▋| 992/14
[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 992:  66%|███████▎   | 992/1495 [06:10<02:55,  2.87it/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>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>Can the details of the background be visible?
A. Hardly visible
B. Totally invisible
C. Clearly visible
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Can the details of the background be visible?
A. Hardly visible
B. Totally invisible
C. Clearly visible
Answer with the option's letter from the given choices directly.

prompts: [["Can the details of the background be visible?\nA. Hardly visible\nB. Totally invisible\nC. Clearly visible\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])
 A.

[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 992:  66%|███████▎   | 993/1495 [06:10<02:52,  2.91it/s]
[Running Accuracy]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: Totally invisible, , [Prog]: 993:  66%|▋| 993/1495 [06:10<02:52,  2.91i
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Can the details of the background be visible?\nA. Hardly visible\nB. Totally invisible\nC. Clearly visible\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

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

prompts: [["Is the penguin prominent in the image?\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]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: Totally invisible, , [Prog]: 993:  66%|▋| 994/1495 [06:10<02:47,  2.99i
[Running Accuracy]: 0.7817,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 994:  66%|███████▎   | 994/1495 [06:10<02:47,  2.99it/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>Is the penguin prominent 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 sky in this picture have overexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the sky in this picture have overexposure issues?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the sky in this picture have overexposure issues?\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]: 0.7817,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 994:  67%|███████▎   | 995/1495 [06:11<03:23,  2.46it/s]
[Running Accuracy]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 995:  67%|███████▎   | 995/1495 [06:11<03:23,  2.46it/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>Does the sky in this picture have overexposure 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>How would you rate the 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 would you rate the clarity of 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 this image?\nA. High\nB. Acceptable\nC. Low\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]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 995:  67%|███████▎   | 996/1495 [06:11<03:10,  2.63it/s]
[Running Accuracy]: 0.7821,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 996:  67%|███████▎   | 996/1495 [06:11<03:10,  2.63it/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 would you rate the clarity of 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 is the worst distortion in this picture?
A. Underexposure
B. Noise
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. Underexposure
B. Noise
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. Underexposure\nB. Noise\nC. Out of focus\nD. Overexposure\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]: 0.7821,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 996:  67%|███████▎   | 997/1495 [06:12<03:02,  2.72it/s]
[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 997:  67%|██████   | 997/1495 [06:12<03:02,  2.72it/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>What is the worst distortion in this picture?\nA. Underexposure\nB. Noise\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 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([-30.9531], 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]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 997:  67%|██████   | 998/1495 [06:12<02:52,  2.88it/s]
[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 998:  67%|████████    | 998/1495 [06:12<02:52,  2.88it/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>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 is the exposure level of 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 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 image?\nA. Moderate\nB. Overexposed\nC. Underexposed\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])
 A.

[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 998:  67%|████████    | 999/1495 [06:12<02:53,  2.86it/s]
[Running Accuracy]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 999:  67%|████  | 999/1495 [06:12<02:53,  2.86it/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>What is the exposure level of 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>Does this picture have overexposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure?\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]: 0.7828,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 999:  67%|███▎ | 1000/1495 [06:13<02:55,  2.83it/s]
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1000:  67%|██████   | 1000/1495 [06:13<02:55,  2.83it/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>Does this picture have overexposure?\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 woman in the image blurred?
A. Very blurred
B. Not blurred at all
C. Slightly blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the woman in the image blurred?
A. Very blurred
B. Not blurred at all
C. Slightly blurred
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the woman in the image blurred?\nA. Very blurred\nB. Not blurred at all\nC. Slightly blurred\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]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1000:  67%|██████   | 1001/1495 [06:13<02:47,  2.95it/s]
[Running Accuracy]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurred, , [Prog]: 1001:  67%|▋| 1001/1495 [06:13<02:47,  2.95
 {'prompt': "A chat 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 woman in the image blurred?\nA. Very blurred\nB. Not blurred at all\nC. Slightly 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>What is the level of frosty artifacts in this image?
A. Strong
B. Weak
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the level of frosty artifacts in this image?
A. Strong
B. Weak
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What is the level of frosty artifacts in this image?\nA. Strong\nB. Weak\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]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Slightly blurred, , [Prog]: 1001:  67%|▋| 1002/1495 [06:13<02:46,  2.96
[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 1002:  67%|████  | 1002/1495 [06:13<02:46,  2.96it/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>What is the level of frosty artifacts in this image?\nA. Strong\nB. Weak\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 in the image rich?
A. Moderate
B. Monotonous
C. Rich
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color in the image rich?
A. Moderate
B. Monotonous
C. Rich
Answer with the option's letter from the given choices directly.

prompts: [["Is the color in the image rich?\nA. Moderate\nB. Monotonous\nC. Rich\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]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Strong, , [Prog]: 1002:  67%|████  | 1003/1495 [06:14<02:46,  2.96it/s]
[Running Accuracy]: 0.7817,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1003:  67%|██▋ | 1003/1495 [06:14<02:46,  2.96it/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>Is the color in the image rich?\nA. Moderate\nB. Monotonous\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>Which part of the image is the sharpest?
A. The stone wall
B. The person's clothes
C. The person's face
D. The path
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the sharpest?
A. The stone wall
B. The person's clothes
C. The person's face
D. The path
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the sharpest?\nA. The stone wall\nB. The person's clothes\nC. The person's face\nD. The path\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]: 0.7817,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1003:  67%|██▋ | 1004/1495 [06:14<02:47,  2.92it/s]
[Running Accuracy]: 0.7819,[Response]: C.<|endoftext|>, [Correct Ans]: The person's face, , [Prog]: 1004:  67%|▋| 1004/1495 [06:14<02:47,  2.9
 {'prompt': "A chat between 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 sharpest?\nA. The stone wall\nB. The person's clothes\nC. The person's face\nD. The path\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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([-30.2188], 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]: 0.7819,[Response]: C.<|endoftext|>, [Correct Ans]: The person's face, , [Prog]: 1004:  67%|▋| 1005/1495 [06:14<02:39,  3.0
[Running Accuracy]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1005:  67%|██████   | 1005/1495 [06:14<02:39,  3.07it/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>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 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([-31.0625], 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]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1005:  67%|██████   | 1006/1495 [06:15<03:19,  2.45it/s]
[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1006:  67%|██████   | 1006/1495 [06:15<03:19,  2.45it/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>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>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([-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])
 B.

[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1006:  67%|██████   | 1007/1495 [06:15<03:09,  2.58it/s]
[Running Accuracy]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1007:  67%|██████   | 1007/1495 [06:15<03:09,  2.58it/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>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': 'B.<|endoftext|>'} 

prompt A chat 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?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have overexposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have overexposure?\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]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1007:  67%|██████   | 1008/1495 [06:16<02:57,  2.74it/s]
[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1008:  67%|██████   | 1008/1495 [06:16<02:57,  2.74it/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>Does this picture have overexposure?\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. 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([-31.2500], 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]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1008:  67%|██████   | 1009/1495 [06:16<03:43,  2.17it/s]
[Running Accuracy]: 0.7830,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1009:  67%|█████▍  | 1009/1495 [06:16<03:43,  2.17it/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 bright is this picture\nA. Normal\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 is the color saturation of the fire 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 fire 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 fire in the image?\nA. Poor\nB. Average\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])
 A.

[Running Accuracy]: 0.7830,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1009:  68%|█████▍  | 1010/1495 [06:17<03:21,  2.41it/s]
[Running Accuracy]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1010:  68%|█████▍  | 1010/1495 [06:17<03:21,  2.41it/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 color saturation of the fire in the image?\nA. Poor\nB. Average\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 is the most apparent distortion for the trees and plants?
A. Motion 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 for the trees and plants?
A. Motion blur
B. Noise
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion for the trees and plants?\nA. Motion blur\nB. Noise\nC. Under-exposure\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])
 A.

[Running Accuracy]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1010:  68%|█████▍  | 1011/1495 [06:17<03:50,  2.10it/s]
[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1011:  68%|▋| 1011/1495 [06:17<03:50,  2.10it/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>What is the most apparent distortion for the trees and plants?\nA. Motion blur\nB. Noise\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 ground tilted in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the ground tilted in this photo?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the ground tilted in this photo?\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]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1011:  68%|▋| 1012/1495 [06:18<04:06,  1.96it/s]
[Running Accuracy]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1012:  68%|██████   | 1012/1495 [06:18<04:06,  1.96it/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>Is the ground tilted in this photo?\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 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([-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]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1012:  68%|██████   | 1013/1495 [06:18<03:41,  2.17it/s]
[Running Accuracy]: 0.7808,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1013:  68%|▋| 1013/1495 [06:18<03:41,  2.17i
 {'prompt': "A chat between 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': 'B.<|endoftext|>'} 

prompt A chat 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([-31.0625], 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]: 0.7808,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1013:  68%|▋| 1014/1495 [06:18<03:15,  2.46i
[Running Accuracy]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1014:  68%|██████   | 1014/1495 [06:18<03:15,  2.46it/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>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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Car
C. Sky
D. Tree
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. Car
C. Sky
D. Tree
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Ground\nB. Car\nC. Sky\nD. Tree\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]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1014:  68%|██████   | 1015/1495 [06:19<03:05,  2.59it/s]
[Running Accuracy]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 1015:  68%|██████   | 1015/1495 [06:19<03:05,  2.59it/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>What is the brightest part in this image?\nA. Ground\nB. Car\nC. Sky\nD. Tree\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 the primary color appearing on the characters in the image?
A. red
B. blue
C. brown
D. green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is not the primary color appearing on the characters in the image?
A. red
B. blue
C. brown
D. green
Answer with the option's letter from the given choices directly.

prompts: [["Which color is not the primary color appearing on the characters in the image?\nA. red\nB. blue\nC. brown\nD. green\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]: 0.7803,[Response]: B.<|endoftext|>, [Correct Ans]: Car, , [Prog]: 1015:  68%|██████   | 1016/1495 [06:19<02:58,  2.69it/s]
[Running Accuracy]: 0.7805,[Response]: A.<|endoftext|>, [Correct Ans]: red, , [Prog]: 1016:  68%|██████   | 1016/1495 [06:19<02:58,  2.69it/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>Which color is not the primary color appearing on the characters in the image?\nA. red\nB. blue\nC. brown\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>Are the characters on the sign clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the characters on the sign clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the characters on the sign 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])
 B.

[Running Accuracy]: 0.7805,[Response]: A.<|endoftext|>, [Correct Ans]: red, , [Prog]: 1016:  68%|██████   | 1017/1495 [06:20<03:28,  2.29it/s]
[Running Accuracy]: 0.7807,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1017:  68%|██████▊   | 1017/1495 [06:20<03:28,  2.29it/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>Are the characters on the sign 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 lighting of the parking sign?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the parking sign?
A. Acceptable
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the parking sign?\nA. Acceptable\nB. Low\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])
 B.

[Running Accuracy]: 0.7807,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1017:  68%|██████▊   | 1018/1495 [06:20<03:44,  2.12it/s]
[Running Accuracy]: 0.7800,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1018:  68%|█▎| 1018/1495 [06:20<03:44,  2.12it/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 lighting of the parking sign?\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>Which object is the focus in the image?
A. shop
B. railing
C. parking sign
D. bus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in the image?
A. shop
B. railing
C. parking sign
D. bus
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in the image?\nA. shop\nB. railing\nC. parking sign\nD. bus\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])
 D.

[Running Accuracy]: 0.7800,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1018:  68%|█▎| 1019/1495 [06:21<03:20,  2.37it/s]
[Running Accuracy]: 0.7802,[Response]: D.<|endoftext|>, [Correct Ans]: bus, , [Prog]: 1019:  68%|██████▏  | 1019/1495 [06:21<03:20,  2.37it/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>Which object is the focus in the image?\nA. shop\nB. railing\nC. parking sign\nD. bus\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 part in this picture?
A. Trees
B. Human
C. Land
D. Waves
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part in this picture?
A. Trees
B. Human
C. Land
D. Waves
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part in this picture?\nA. Trees\nB. Human\nC. Land\nD. Waves\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]: 0.7802,[Response]: D.<|endoftext|>, [Correct Ans]: bus, , [Prog]: 1019:  68%|██████▏  | 1020/1495 [06:21<03:07,  2.53it/s]
[Running Accuracy]: 0.7804,[Response]: B.<|endoftext|>, [Correct Ans]: Human, , [Prog]: 1020:  68%|████▊  | 1020/1495 [06:21<03:07,  2.53it/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>What is the clearest part in this picture?\nA. Trees\nB. Human\nC. Land\nD. Waves\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

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

prompts: [["What is the level of blurriness in the image?\nA. Completely blurry\nB. Slightly blurry\nC. Very blurry\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]: 0.7804,[Response]: B.<|endoftext|>, [Correct Ans]: Human, , [Prog]: 1020:  68%|████▊  | 1021/1495 [06:21<02:56,  2.69it/s]
[Running Accuracy]: 0.7806,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1021:  68%|▋| 1021/1495 [06:21<02:56,  2.69i
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What is the level of blurriness in the image?\nA. Completely blurry\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>What kind of visual feelings does the image give?
A. Fresh
B. Gloomy
C. Cheerful
D. Happy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feelings does the image give?
A. Fresh
B. Gloomy
C. Cheerful
D. Happy
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feelings does the image give?\nA. Fresh\nB. Gloomy\nC. Cheerful\nD. Happy\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]: 0.7806,[Response]: B.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1021:  68%|▋| 1022/1495 [06:21<02:47,  2.82i
[Running Accuracy]: 0.7808,[Response]: B.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 1022:  68%|████  | 1022/1495 [06:21<02:47,  2.82it/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>What kind of visual feelings does the image give?\nA. Fresh\nB. Gloomy\nC. Cheerful\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>Which object is emphasized in the composition of the image?
A. Clothing
B. Person
C. Door
D. Railing
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. Clothing
B. Person
C. Door
D. Railing
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Clothing\nB. Person\nC. Door\nD. Railing\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]: 0.7808,[Response]: B.<|endoftext|>, [Correct Ans]: Gloomy, , [Prog]: 1022:  68%|████  | 1023/1495 [06:22<02:42,  2.90it/s]
[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1023:  68%|████  | 1023/1495 [06:22<02:42,  2.90it/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>Which object is emphasized in the composition of the image?\nA. Clothing\nB. Person\nC. Door\nD. Railing\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Dead tree branch
B. Large tree
C. Sky
D. Bicycle
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Dead tree branch
B. Large tree
C. Sky
D. Bicycle
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Dead tree branch\nB. Large tree\nC. Sky\nD. Bicycle\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])
 D.

[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1023:  68%|████  | 1024/1495 [06:22<02:39,  2.96it/s]
[Running Accuracy]: 0.7812,[Response]: D.<|endoftext|>, [Correct Ans]: Bicycle, , [Prog]: 1024:  68%|███▍ | 1024/1495 [06:22<02:39,  2.96it/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>What is the brightest part in this image?\nA. Dead tree branch\nB. Large tree\nC. Sky\nD. Bicycle\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 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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.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]: D.<|endoftext|>, [Correct Ans]: Bicycle, , [Prog]: 1024:  69%|███▍ | 1025/1495 [06:22<02:38,  2.97it/s]
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1025:  69%|██████▏  | 1025/1495 [06:22<02:38,  2.97it/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>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 worst distortion in this picture?
A. Out of focus
B. Motion blur
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. Motion blur
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. Motion blur\nC. Noise\nD. Overexposure\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]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1025:  69%|██████▏  | 1026/1495 [06:23<02:35,  3.02it/s]
[Running Accuracy]: 0.7807,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1026:  69%|▋| 1026/1495 [06:23<02:35,  3.02it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\nC. Noise\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 the window brighter than the room?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the window brighter than the room?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the window brighter than the room?\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]: 0.7807,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1026:  69%|▋| 1027/1495 [06:23<02:32,  3.06it/s]
[Running Accuracy]: 0.7809,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1027:  69%|██████▏  | 1027/1495 [06:23<02:32,  3.06it/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>Is the window brighter than the room?\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 detail on the toothpaste clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the detail on the toothpaste clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the detail on the toothpaste clear?\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]: 0.7809,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1027:  69%|██████▏  | 1028/1495 [06:23<02:30,  3.10it/s]
[Running Accuracy]: 0.7802,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1028:  69%|██████▉   | 1028/1495 [06:23<02:30,  3.10it/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>Is the detail on the toothpaste 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 focus of this image?
A. The man sleeping
B. The chair
C. The man playing computer
D. The curtain
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the focus of this image?
A. The man sleeping
B. The chair
C. The man playing computer
D. The curtain
Answer with the option's letter from the given choices directly.

prompts: [["What is the focus of this image?\nA. The man sleeping\nB. The chair\nC. The man playing computer\nD. The curtain\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]: 0.7802,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1028:  69%|██████▉   | 1029/1495 [06:24<02:29,  3.12it/s]
[Running Accuracy]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: The man sleeping, , [Prog]: 1029:  69%|▋| 1029/1495 [06:24<02:29,  3.12
 {'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>What is the focus of this image?\nA. The man sleeping\nB. The chair\nC. The man playing computer\nD. The curtain\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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. Road
B. Vehicles
C. People and bicycles
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. Road
B. Vehicles
C. People and bicycles
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. Road\nB. Vehicles\nC. People and bicycles\nD. Building\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]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: The man sleeping, , [Prog]: 1029:  69%|▋| 1030/1495 [06:24<02:29,  3.11
[Running Accuracy]: 0.7806,[Response]: C.<|endoftext|>, [Correct Ans]: People and bicycles, , [Prog]: 1030:  69%|▋| 1030/1495 [06:24<02:29,  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 emphasized in the composition of the image?\nA. Road\nB. Vehicles\nC. People and bicycles\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 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([-31.3750], 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]: 0.7806,[Response]: C.<|endoftext|>, [Correct Ans]: People and bicycles, , [Prog]: 1030:  69%|▋| 1031/1495 [06:24<02:29,  3
[Running Accuracy]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1031:  69%|██████▏  | 1031/1495 [06:24<02:29,  3.10it/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 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>How blurry is the image?
A. Very blurry
B. Not blurry at all
C. Slightly 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. Slightly 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. Slightly 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]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1031:  69%|██████▏  | 1032/1495 [06:25<02:26,  3.16it/s]
[Running Accuracy]: 0.7810,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1032:  69%|▋| 1032/1495 [06:25<02:26,  3.16i
 {'prompt': "A chat between 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. 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>Which object is the focus in the image?
A. Pedestrian
B. The woman in a white dress and the man in a black suit
C. Poster
D. Floor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in the image?
A. Pedestrian
B. The woman in a white dress and the man in a black suit
C. Poster
D. Floor
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in the image?\nA. Pedestrian\nB. The woman in a white dress and the man in a black suit\nC. Poster\nD. Floor\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]: 0.7810,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1032:  69%|▋| 1033/1495 [06:25<02:27,  3.12i
[Running Accuracy]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: The woman in a white dress and the man in a black suit, , [Prog]: 1033:
 {'prompt': "A chat between 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 the image?\nA. Pedestrian\nB. The woman in a white dress and the man in a black suit\nC. Poster\nD. Floor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 hanging 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 hanging 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 hanging lantern in this image vibrant?\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]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: The woman in a white dress and the man in a black suit, , [Prog]: 1033:
[Running Accuracy]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1034:  69%|██████▏  | 1034/1495 [06:25<02:26,  3.15it/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>Is the color of the hanging lantern 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 is the color saturation 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 color saturation of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of this image?\nA. High\nB. Medium\nC. Low\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]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1034:  69%|██████▏  | 1035/1495 [06:26<02:31,  3.03it/s]
[Running Accuracy]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1035:  69%|█████▌  | 1035/1495 [06:26<02:31,  3.03it/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 color saturation of this 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 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([-30.2969], 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]: 0.7816,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1035:  69%|█████▌  | 1036/1495 [06:26<02:28,  3.08it/s]
[Running Accuracy]: 0.7809,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1036:  69%|████▏ | 1036/1495 [06:26<02:28,  3.08it/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 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': 'B.<|endoftext|>'} 

prompt A chat 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 emphasized in composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the flowers emphasized in composition of the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the flowers emphasized in composition of the image?\nA. Yes\nB. No\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]: 0.7809,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1036:  69%|████▏ | 1037/1495 [06:27<03:07,  2.45it/s]
[Running Accuracy]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1037:  69%|██████▏  | 1037/1495 [06:27<03:07,  2.45it/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>Are the flowers emphasized in 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>How is the arrangement of elements in this image?
A. Acceptable
B. Good
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the arrangement of elements in this image?
A. Acceptable
B. Good
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the arrangement of elements in this image?\nA. Acceptable\nB. Good\nC. Bad\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]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1037:  69%|██████▏  | 1038/1495 [06:27<02:54,  2.62it/s]
[Running Accuracy]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1038:  69%|█████▌  | 1038/1495 [06:27<02:54,  2.62it/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 arrangement of elements in this image?\nA. Acceptable\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 would you describe the richness in the color of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you describe the richness in the color of the image?
A. Good
B. Poor
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How would you describe the richness in the color of the image?\nA. Good\nB. Poor\nC. Fair\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]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1038:  69%|█████▌  | 1039/1495 [06:27<02:45,  2.76it/s]
[Running Accuracy]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1039:  69%|█████▌  | 1039/1495 [06:27<02:45,  2.76it/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 would you describe the richness in the color 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>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([-31.5469], 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]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1039:  70%|█████▌  | 1040/1495 [06:28<02:42,  2.81it/s]
[Running Accuracy]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1040:  70%|██████▎  | 1040/1495 [06:28<02:42,  2.81it/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 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 the main subject brighter than the background, or darker than the background?
A. Darker
B. Brighter
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject brighter than the background, or darker than the background?
A. Darker
B. Brighter
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject brighter than the background, or darker than the background?\nA. Darker\nB. Brighter\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]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1040:  70%|██████▎  | 1041/1495 [06:28<02:44,  2.76it/s]
[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Brighter, , [Prog]: 1041:  70%|██▊ | 1041/1495 [06:28<02:44,  2.76it/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>Is the main subject brighter than the background, or darker than the background?\nA. Darker\nB. Brighter\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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([-31.0781], 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]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Brighter, , [Prog]: 1041:  70%|██▊ | 1042/1495 [06:28<02:37,  2.87it/s]
[Running Accuracy]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1042:  70%|██████▉   | 1042/1495 [06:28<02:37,  2.87it/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>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>How about the exposure of the chair?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How about the exposure of the chair?
A. Just fine
B. Too dark
C. Too bright
Answer with the option's letter from the given choices directly.

prompts: [["How about the exposure of the chair?\nA. Just fine\nB. Too dark\nC. Too bright\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]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1042:  70%|██████▉   | 1043/1495 [06:29<02:36,  2.88it/s]
[Running Accuracy]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1043:  70%|██▊ | 1043/1495 [06:29<02:36,  2.88it/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 about the exposure of the chair?\nA. Just fine\nB. Too dark\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>How is the color of the snow in this image?
A. Monotonous
B. Vivid
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the snow in this image?
A. Monotonous
B. Vivid
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the snow in this image?\nA. Monotonous\nB. Vivid\nC. Moderate\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]: 0.7814,[Response]: B.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1043:  70%|██▊ | 1044/1495 [06:29<02:30,  3.00it/s]
[Running Accuracy]: 0.7807,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1044:  70%|█▍| 1044/1495 [06:29<02:30,  3.00it/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 color of the snow in this image?\nA. Monotonous\nB. Vivid\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 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([-31.3125], 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]: 0.7807,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1044:  70%|█▍| 1045/1495 [06:29<02:26,  3.06it/s]
[Running Accuracy]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1045:  70%|██████▎  | 1045/1495 [06:29<02:26,  3.06it/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>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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Compression
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. Compression
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. Compression\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]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1045:  70%|██████▎  | 1046/1495 [06:30<02:25,  3.09it/s]
[Running Accuracy]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1046:  70%|█████▌  | 1046/1495 [06:30<02:25,  3.09it/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>What is the major distortion in this image?\nA. Noise\nB. Blur\nC. Compression\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 ducks 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 clarity of the ducks in this image?
A. Acceptable
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the ducks in this image?\nA. Acceptable\nB. High\nC. Low\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]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1046:  70%|█████▌  | 1047/1495 [06:30<02:23,  3.13it/s]
[Running Accuracy]: 0.7803,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1047:  70%|██████▎  | 1047/1495 [06:30<02:23,  3.13it/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 clarity of the ducks 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>What is the degree of blurriness of the image?
A. Very blurry
B. Somewhat 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. Very blurry
B. Somewhat 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. Very blurry\nB. Somewhat blurry\nC. Not blurry 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])
 B.

[Running Accuracy]: 0.7803,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1047:  70%|██████▎  | 1048/1495 [06:30<02:21,  3.15it/s]
[Running Accuracy]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1048:  70%|▋| 1048/1495 [06:30<02:21,  3.15it/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>What is the degree of blurriness of the image?\nA. Very blurry\nB. Somewhat 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 there any visible light reflection in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any visible light reflection in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any visible light reflection in the image?\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]: 0.7796,[Response]: B.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1048:  70%|▋| 1049/1495 [06:31<02:59,  2.49it/s]
[Running Accuracy]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1049:  70%|██████▎  | 1049/1495 [06:31<02:59,  2.49it/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>Is there any visible light reflection 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 image with severe noise on the smartphone?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image with severe noise on the smartphone?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image with severe noise on the smartphone?\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]: 0.7798,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1049:  70%|██████▎  | 1050/1495 [06:31<03:28,  2.14it/s]
[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1050:  70%|███████   | 1050/1495 [06:31<03:28,  2.14it/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>Is this image with severe noise on the smartphone?\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 food in 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 noise level of the food in 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 noise level of the food in this image?\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]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1050:  70%|███████   | 1051/1495 [06:32<03:07,  2.37it/s]
[Running Accuracy]: 0.7802,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1051:  70%|█████▌  | 1051/1495 [06:32<03:07,  2.37it/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 would you rate the noise level of the food 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>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([-31.2969], 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]: 0.7802,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1051:  70%|█████▋  | 1052/1495 [06:32<02:55,  2.53it/s]
[Running Accuracy]: 0.7804,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1052:  70%|██▊ | 1052/1495 [06:32<02:55,  2.53it/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 colorful is this picture?\nA. Normal\nB. Dull\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 clear is 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 image?
A. Clear
B. Blurry
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Clear\nB. Blurry\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])
 A.

[Running Accuracy]: 0.7804,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1052:  70%|██▊ | 1053/1495 [06:32<02:45,  2.67it/s]
[Running Accuracy]: 0.7797,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1053:  70%|██▊ | 1053/1495 [06:32<02:45,  2.67it/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 clear is 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>Which of the following quality issues does this image not have?
A. Overexposure
B. Underexposure
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 this image not have?
A. Overexposure
B. Underexposure
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 this image not have?\nA. Overexposure\nB. Underexposure\nC. Noise\nD. Out-of-focus\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1719], 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]: 0.7797,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1053:  71%|██▊ | 1054/1495 [06:33<02:37,  2.79it/s]
[Running Accuracy]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1054:  71%|▋| 1054/1495 [06:33<02:37,  2.79it/
 {'prompt': "A chat between 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. Underexposure\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>Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\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]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1054:  71%|▋| 1055/1495 [06:33<03:16,  2.24it/
[Running Accuracy]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1055:  71%|███████   | 1055/1495 [06:33<03:16,  2.24it/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>Does this picture have underexposure 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>How is the brightness level of the characters in the image?
A. Too bright
B. Moderate
C. Too dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness level of the characters in the image?
A. Too bright
B. Moderate
C. Too dark
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness level of the characters in the image?\nA. Too bright\nB. Moderate\nC. Too 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]: 0.7801,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1055:  71%|███████   | 1056/1495 [06:34<02:59,  2.44it/s]
[Running Accuracy]: 0.7803,[Response]: C.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1056:  71%|██▊ | 1056/1495 [06:34<02:59,  2.44it/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 brightness level of the characters in the image?\nA. Too bright\nB. Moderate\nC. Too 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. 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([-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]: 0.7803,[Response]: C.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1056:  71%|██▊ | 1057/1495 [06:34<02:44,  2.66it/s]
[Running Accuracy]: 0.7805,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1057:  71%|█████▋  | 1057/1495 [06:34<02:44,  2.66it/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 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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 of this picture?
A. Clothes
B. People
C. Cloest
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main object of this picture?
A. Clothes
B. People
C. Cloest
Answer with the option's letter from the given choices directly.

prompts: [["What is the main object of this picture?\nA. Clothes\nB. People\nC. Cloest\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]: 0.7805,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1057:  71%|█████▋  | 1058/1495 [06:34<02:36,  2.79it/s]
[Running Accuracy]: 0.7807,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1058:  71%|████▏ | 1058/1495 [06:34<02:36,  2.79it/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>What is the main object of this picture?\nA. Clothes\nB. People\nC. Cloest\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 a blur problem?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have a blur problem?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have a blur problem?\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]: 0.7807,[Response]: B.<|endoftext|>, [Correct Ans]: People, , [Prog]: 1058:  71%|████▎ | 1059/1495 [06:35<02:31,  2.88it/s]
[Running Accuracy]: 0.7809,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1059:  71%|███████   | 1059/1495 [06:35<02:31,  2.88it/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>Does the image have a blur problem?\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 this image a dog?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the brightest part of this image a dog?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the brightest part of this image a dog?\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])
 A.

[Running Accuracy]: 0.7809,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1059:  71%|███████   | 1060/1495 [06:35<02:28,  2.92it/s]
[Running Accuracy]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1060:  71%|███████   | 1060/1495 [06:35<02:28,  2.92it/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>Is the brightest part of this image a dog?\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 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([-31.3594], 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]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1060:  71%|███████   | 1061/1495 [06:35<02:46,  2.61it/s]
[Running Accuracy]: 0.7813,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1061:  71%|█████▋  | 1061/1495 [06:35<02:46,  2.61it/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 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>Which object in this image composition is emphasized in the central position?
A. Onlookers
B. Police
C. Handrail
D. Warning sign
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image composition is emphasized in the central position?
A. Onlookers
B. Police
C. Handrail
D. Warning sign
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image composition is emphasized in the central position?\nA. Onlookers\nB. Police\nC. Handrail\nD. Warning sign\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]: 0.7813,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1061:  71%|█████▋  | 1062/1495 [06:36<02:37,  2.75it/s]
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Police, , [Prog]: 1062:  71%|████▎ | 1062/1495 [06:36<02:37,  2.75it/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>Which object in this image composition is emphasized in the central position?\nA. Onlookers\nB. Police\nC. Handrail\nD. Warning sign\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 too bright?
A. The left part
B. The right part
C. The middle part
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is too bright?
A. The left part
B. The right part
C. The middle part
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is too bright?\nA. The left part\nB. The right part\nC. The middle part\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]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Police, , [Prog]: 1062:  71%|████▎ | 1063/1495 [06:36<02:33,  2.82it/s]
[Running Accuracy]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: The right part, , [Prog]: 1063:  71%|▋| 1063/1495 [06:36<02:33,  2.82it
 {'prompt': "A chat between 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 too bright?\nA. The left part\nB. The right part\nC. The middle 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 lighting of the rocks?
A. Low
B. Good
C. Meidum
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the rocks?
A. Low
B. Good
C. Meidum
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the rocks?\nA. Low\nB. Good\nC. Meidum\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]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: The right part, , [Prog]: 1063:  71%|▋| 1064/1495 [06:37<03:04,  2.33it
[Running Accuracy]: 0.7820,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1064:  71%|█████▋  | 1064/1495 [06:37<03:04,  2.33it/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 lighting of the rocks?\nA. Low\nB. Good\nC. Meidum\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a 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 correctly on the main subject?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus in the image correctly on the main subject?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus in the image correctly on the main subject?\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]: 0.7820,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1064:  71%|█████▋  | 1065/1495 [06:37<02:49,  2.53it/s]
[Running Accuracy]: 0.7822,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1065:  71%|██████▍  | 1065/1495 [06:37<02:49,  2.53it/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>Is the focus in the image correctly on 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>In the composition of this image, is the robot 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 this image, is the robot emphasized in the center?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of this image, is the robot emphasized in the center?\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]: 0.7822,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1065:  71%|██████▍  | 1066/1495 [06:37<02:37,  2.73it/s]
[Running Accuracy]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1066:  71%|██████▍  | 1066/1495 [06:37<02:37,  2.73it/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>In the composition of this image, is the robot 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>How would you rate the clarity of this image?
A. Low
B. High
C. Acceptable
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. Acceptable
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. Acceptable\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]: 0.7824,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1066:  71%|██████▍  | 1067/1495 [06:38<02:29,  2.86it/s]
[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1067:  71%|██████▍  | 1067/1495 [06:38<02:29,  2.86it/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 would you rate the clarity of this image?\nA. Low\nB. High\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>What is the most apparent distortion of the cars in this image?
A. Over-exposure
B. Motion blur
C. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most apparent distortion of the cars in this image?
A. Over-exposure
B. Motion blur
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of the cars in this image?\nA. Over-exposure\nB. Motion blur\nC. 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])
 B.

[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1067:  71%|██████▍  | 1068/1495 [06:38<02:23,  2.97it/s]
[Running Accuracy]: 0.7828,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1068:  71%|▋| 1068/1495 [06:38<02:23,  2.97it/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>What is the most apparent distortion of the cars in this image?\nA. Over-exposure\nB. Motion 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>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([-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]: 0.7828,[Response]: B.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1068:  72%|▋| 1069/1495 [06:38<02:56,  2.42it/s]
[Running Accuracy]: 0.7830,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1069:  72%|██████▍  | 1069/1495 [06:38<02:56,  2.42it/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>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 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([-31.0156], 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]: 0.7830,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1069:  72%|██████▍  | 1070/1495 [06:39<02:38,  2.69it/s]
[Running Accuracy]: 0.7832,[Response]: B<|endoftext|>, [Correct Ans]: No, , [Prog]: 1070:  72%|███████▊   | 1070/1495 [06:39<02:38,  2.69it/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>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>Is this image bright and cheerful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image bright and cheerful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image bright and cheerful?\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])
 B.

[Running Accuracy]: 0.7832,[Response]: B<|endoftext|>, [Correct Ans]: No, , [Prog]: 1070:  72%|███████▉   | 1071/1495 [06:39<02:30,  2.81it/s]
[Running Accuracy]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1071:  72%|███████▏  | 1071/1495 [06:39<02:30,  2.81it/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>Is this image bright and cheerful?\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 saturation of 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 saturation of the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of 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]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1071:  72%|███████▏  | 1072/1495 [06:39<02:26,  2.89it/s]
[Running Accuracy]: 0.7836,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1072:  72%|█████▋  | 1072/1495 [06:39<02:26,  2.89it/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 saturation of 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>How is the color saturation in 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 in 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 in the image?\nA. Low\nB. High\nC. Medium\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]: 0.7836,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1072:  72%|█████▋  | 1073/1495 [06:40<02:24,  2.91it/s]
[Running Accuracy]: 0.7829,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1073:  72%|██████▍  | 1073/1495 [06:40<02:24,  2.91it/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 color saturation in the 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 color saturation 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 color saturation in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation in the image?\nA. Medium\nB. Low\nC. High\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]: 0.7829,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1073:  72%|██████▍  | 1074/1495 [06:40<02:21,  2.96it/s]
[Running Accuracy]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1074:  72%|██████▍  | 1074/1495 [06:40<02:21,  2.96it/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 color saturation in the 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>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([-30.8750], 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]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1074:  72%|██████▍  | 1075/1495 [06:40<02:20,  2.98it/s]
[Running Accuracy]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1075:  72%|██████▍  | 1075/1495 [06:40<02:20,  2.98it/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>Does this picture have overexposure 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>Is the color vibrant in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color vibrant in this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color vibrant in this picture?\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]: 0.7823,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1075:  72%|██████▍  | 1076/1495 [06:41<02:16,  3.06it/s]
[Running Accuracy]: 0.7825,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1076:  72%|███████▏  | 1076/1495 [06:41<02:16,  3.06it/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>Is the color vibrant in 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>To what extent is the image of the little boy in this picture blurry?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the image of the little boy in this picture blurry?
A. Severe
B. Slight
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the image of the little boy in this picture blurry?\nA. Severe\nB. Slight\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]: 0.7825,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1076:  72%|███████▏  | 1077/1495 [06:41<02:16,  3.07it/s]
[Running Accuracy]: 0.7818,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1077:  72%|██▉ | 1077/1495 [06:41<02:16,  3.07it/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>To what extent is the image of the little boy in this picture blurry?\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 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([-31.4844], 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]: 0.7818,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1077:  72%|██▉ | 1078/1495 [06:41<02:14,  3.10it/s]
[Running Accuracy]: 0.7811,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1078:  72%|███████▏  | 1078/1495 [06:41<02:14,  3.10it/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>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>How is the brightness of the small dog in the image?
A. Dark
B. Bright
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the brightness of the small dog in the image?
A. Dark
B. Bright
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the small dog in the image?\nA. Dark\nB. Bright\nC. Average\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]: 0.7811,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1078:  72%|███████▏  | 1079/1495 [06:42<02:13,  3.11it/s]
[Running Accuracy]: 0.7813,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1079:  72%|█████▊  | 1079/1495 [06:42<02:13,  3.11it/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 brightness of the small dog in the image?\nA. Dark\nB. Bright\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 there visible artifacts on the oven below?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there visible artifacts on the oven below?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there visible artifacts on the oven below?\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]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1079:  72%|█████▊  | 1080/1495 [06:42<02:11,  3.15it/s]
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1080:  72%|██████▌  | 1080/1495 [06:42<02:11,  3.15it/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>Are there visible artifacts on the oven below?\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 feeling does the image evoke?
A. Dull
B. Lively
C. Joyful
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does the image evoke?
A. Dull
B. Lively
C. Joyful
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does the image evoke?\nA. Dull\nB. Lively\nC. Joyful\nD. Fresh\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]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1080:  72%|██████▌  | 1081/1495 [06:42<02:11,  3.14it/s]
[Running Accuracy]: 0.7817,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1081:  72%|█████▊  | 1081/1495 [06:42<02:11,  3.14it/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>What kind of feeling does the image evoke?\nA. Dull\nB. Lively\nC. Joyful\nD. Fresh\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurry due to motion?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurry due to motion?\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]: 0.7817,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1081:  72%|█████▊  | 1082/1495 [06:43<02:11,  3.15it/s]
[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1082:  72%|███████▏  | 1082/1495 [06:43<02:11,  3.15it/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>Is the image blurry 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 clear is the dog in 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 the dog in this picture?
A. Clear
B. Fair
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the dog in this picture?\nA. Clear\nB. Fair\nC. Blurry\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])
 C.

[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1082:  72%|███████▏  | 1083/1495 [06:43<02:47,  2.46it/s]
[Running Accuracy]: 0.7812,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1083:  72%|████▎ | 1083/1495 [06:43<02:47,  2.46it/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 clear is the dog in 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>What is the degree of blurriness 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
What is the degree of blurriness 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: [["What is the degree of blurriness 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([-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]: 0.7812,[Response]: C.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1083:  73%|████▎ | 1084/1495 [06:44<02:37,  2.62it/s]
[Running Accuracy]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1084:  73%|▋| 1084/1495 [06:44<02:37,  2.6
 {'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>What is the degree of blurriness 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': 'A.<|endoftext|>'} 

prompt A chat between a 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 bright enough to see clearly?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the christmas tree bright enough to see clearly?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the christmas tree bright enough to see clearly?\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]: 0.7804,[Response]: A.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1084:  73%|▋| 1085/1495 [06:44<02:28,  2.7
[Running Accuracy]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1085:  73%|███████▎  | 1085/1495 [06:44<02:28,  2.77it/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>Is the christmas tree bright enough to see clearly?\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 focus in the center?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the focus in the center?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the focus in the center?\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]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1085:  73%|███████▎  | 1086/1495 [06:44<02:23,  2.86it/s]
[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1086:  73%|██████▌  | 1086/1495 [06:44<02:23,  2.86it/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>Is the focus 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 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([-30.8594], 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]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1086:  73%|██████▌  | 1087/1495 [06:45<02:31,  2.69it/s]
[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1087:  73%|██████▌  | 1087/1495 [06:45<02:31,  2.69it/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>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>Which object is emphasized in the center of this image?
A. The blue sky
B. The flying person
C. The mountains
D. The river
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. The blue sky
B. The flying person
C. The mountains
D. The river
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. The blue sky\nB. The flying person\nC. The mountains\nD. The river\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]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1087:  73%|██████▌  | 1088/1495 [06:45<02:30,  2.70it/s]
[Running Accuracy]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: The flying person, , [Prog]: 1088:  73%|▋| 1088/1495 [06:45<02:30,  2.7
 {'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 is emphasized in the center of this image?\nA. The blue sky\nB. The flying person\nC. The mountains\nD. The river\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 provide?
A. Tranquil
B. Sinister
C. Prosperous
D. Lively
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual perception does the image provide?
A. Tranquil
B. Sinister
C. Prosperous
D. Lively
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual perception does the image provide?\nA. Tranquil\nB. Sinister\nC. Prosperous\nD. Lively\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]: 0.7812,[Response]: B.<|endoftext|>, [Correct Ans]: The flying person, , [Prog]: 1088:  73%|▋| 1089/1495 [06:45<02:24,  2.8
[Running Accuracy]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: Tranquil, , [Prog]: 1089:  73%|██▉ | 1089/1495 [06:45<02:24,  2.81it/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>What kind of visual perception does the image provide?\nA. Tranquil\nB. Sinister\nC. Prosperous\nD. Lively\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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([-31.0938], 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]: 0.7815,[Response]: A.<|endoftext|>, [Correct Ans]: Tranquil, , [Prog]: 1089:  73%|██▉ | 1090/1495 [06:46<02:19,  2.90it/s]
[Running Accuracy]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1090:  73%|██████▌  | 1090/1495 [06:46<02:19,  2.90it/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>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>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([-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]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1090:  73%|██████▌  | 1091/1495 [06:46<02:15,  2.97it/s]
[Running Accuracy]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1091:  73%|███████▎  | 1091/1495 [06:46<02:15,  2.97it/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>Does this picture have noise?\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 blur exists in the windows in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What degree of blur exists in the windows in this image?
A. Severe
B. Moderate
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["What degree of blur exists in the windows in this image?\nA. Severe\nB. Moderate\nC. Slight\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]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1091:  73%|███████▎  | 1092/1495 [06:46<02:15,  2.98it/s]
[Running Accuracy]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1092:  73%|████▍ | 1092/1495 [06:46<02:15,  2.98it/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>What degree of blur exists in the windows 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>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([-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]: 0.7821,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1092:  73%|████▍ | 1093/1495 [06:47<02:13,  3.00it/s]
[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1093:  73%|███████▎  | 1093/1495 [06:47<02:13,  3.00it/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>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>What kind of quality issues exist in the image?
A. Out of focus
B. Motion blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of quality issues exist in the image?
A. Out of focus
B. Motion blur
C. Overexposure
D. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What kind of quality issues exist in the image?\nA. Out of focus\nB. Motion blur\nC. Overexposure\nD. Noise\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]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1093:  73%|███████▎  | 1094/1495 [06:47<02:12,  3.03it/s]
[Running Accuracy]: 0.7824,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1094:  73%|█████  | 1094/1495 [06:47<02:12,  3.03it/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>What kind of quality issues exist in the image?\nA. Out of focus\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>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([-30.9844], 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]: 0.7824,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1094:  73%|█████▏ | 1095/1495 [06:47<02:08,  3.11it/s]
[Running Accuracy]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1095:  73%|█████▊  | 1095/1495 [06:47<02:08,  3.11it/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 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 is the lighting of this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this picture?
A. Normal
B. Dark
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this picture?\nA. Normal\nB. Dark\nC. Bright\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]: 0.7826,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1095:  73%|█████▊  | 1096/1495 [06:48<02:07,  3.12it/s]
[Running Accuracy]: 0.7828,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1096:  73%|████▍ | 1096/1495 [06:48<02:07,  3.12it/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 lighting of this picture?\nA. Normal\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>Is the image quality affected by the rain?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image quality affected by the rain?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image quality affected by the rain?\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]: 0.7828,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1096:  73%|████▍ | 1097/1495 [06:48<02:06,  3.14it/s]
[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1097:  73%|██████▌  | 1097/1495 [06:48<02:06,  3.14it/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>Is the image quality affected by the rain?\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 overall quality of this image?
A. Medium
B. High
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall quality of this image?
A. Medium
B. High
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall quality of this image?\nA. Medium\nB. High\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])
 C.

[Running Accuracy]: 0.7830,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1097:  73%|██████▌  | 1098/1495 [06:48<02:06,  3.14it/s]
[Running Accuracy]: 0.7832,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1098:  73%|█████▉  | 1098/1495 [06:48<02:06,  3.14it/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 overall quality of this image?\nA. Medium\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 is the worst distortion in this picture?
A. Overexposure
B. Out of focus
C. Brightness
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. Overexposure
B. Out of focus
C. Brightness
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Brightness\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])
 B.

[Running Accuracy]: 0.7832,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1098:  74%|█████▉  | 1099/1495 [06:49<02:52,  2.29it/s]
[Running Accuracy]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1099:  74%|▋| 1099/1495 [06:49<02:52,  2.29it/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>What is the worst distortion in this picture?\nA. Overexposure\nB. Out of focus\nC. Brightness\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 kind of visual impression does this image give?
A. bright
B. happy
C. fresh
D. dull
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual impression does this image give?
A. bright
B. happy
C. fresh
D. dull
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does this image give?\nA. bright\nB. happy\nC. fresh\nD. dull\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])
 D.

[Running Accuracy]: 0.7834,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1099:  74%|▋| 1100/1495 [06:49<02:40,  2.46it/s
[Running Accuracy]: 0.7836,[Response]: D.<|endoftext|>, [Correct Ans]: dull, , [Prog]: 1100:  74%|█████▉  | 1100/1495 [06:49<02:40,  2.46it/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>What kind of visual impression does this image give?\nA. bright\nB. happy\nC. fresh\nD. dull\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 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([-31.1875], 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]: 0.7836,[Response]: D.<|endoftext|>, [Correct Ans]: dull, , [Prog]: 1100:  74%|█████▉  | 1101/1495 [06:50<02:35,  2.53it/s]
[Running Accuracy]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1101:  74%|█████▉  | 1101/1495 [06:50<02:35,  2.53it/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 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 blurry is the horse in the image?
A. Very blurry
B. Not blurry at all
C. A little blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the horse in the image?
A. Very blurry
B. Not blurry at all
C. A little blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the horse in the image?\nA. Very blurry\nB. Not blurry at all\nC. A little blurry\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]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1101:  74%|█████▉  | 1102/1495 [06:50<02:30,  2.61it/s]
[Running Accuracy]: 0.7831,[Response]: A.<|endoftext|>, [Correct Ans]: A little blurry, , [Prog]: 1102:  74%|▋| 1102/1495 [06:50<02:30,  2.61i
 {'prompt': "A chat between 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 horse in the image?\nA. Very blurry\nB. Not blurry at all\nC. A little 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 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([-30.8906], 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]: 0.7831,[Response]: A.<|endoftext|>, [Correct Ans]: A little blurry, , [Prog]: 1102:  74%|▋| 1103/1495 [06:50<02:26,  2.68i
[Running Accuracy]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1103:  74%|███▋ | 1103/1495 [06:50<02:26,  2.68it/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 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>Does the blood of the man look realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the blood of the man look realistic?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the blood of the man look realistic?\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]: 0.7824,[Response]: B.<|endoftext|>, [Correct Ans]: Average, , [Prog]: 1103:  74%|███▋ | 1104/1495 [06:51<02:23,  2.73it/s]
[Running Accuracy]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1104:  74%|███████▍  | 1104/1495 [06:51<02:23,  2.73it/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>Does the blood of the man look 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 is the lighting 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 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 this image?\nA. Bright\nB. Medium\nC. Dark\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]: 0.7817,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1104:  74%|███████▍  | 1105/1495 [06:51<02:20,  2.78it/s]
[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1105:  74%|█████▉  | 1105/1495 [06:51<02:20,  2.78it/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 lighting of 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>Is the saturation of the sunflower high in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the saturation of the sunflower high in the image?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["Is the saturation of the sunflower high in the image?\nA. Medium\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])
 C.

[Running Accuracy]: 0.7810,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1105:  74%|█████▉  | 1106/1495 [06:51<02:15,  2.86it/s]
[Running Accuracy]: 0.7812,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1106:  74%|█████▉  | 1106/1495 [06:51<02:15,  2.86it/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>Is the saturation of the sunflower high 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>Are the people in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in the image clear?\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])
 A.

[Running Accuracy]: 0.7812,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1106:  74%|█████▉  | 1107/1495 [06:52<02:13,  2.90it/s]
[Running Accuracy]: 0.7814,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1107:  74%|███████▍  | 1107/1495 [06:52<02:13,  2.90it/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>Are the people 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>Is there any issue of motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there any issue of motion blur in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any issue of motion blur in the image?\nA. Yes\nB. No\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]: 0.7814,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1107:  74%|███████▍  | 1108/1495 [06:52<02:13,  2.89it/s]
[Running Accuracy]: 0.7816,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1108:  74%|███████▍  | 1108/1495 [06:52<02:13,  2.89it/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>Is there any issue of motion blur 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's the focus in this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the focus in this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How's the focus in this image?\nA. Medium\nB. Good\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])
 C.

[Running Accuracy]: 0.7816,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1108:  74%|███████▍  | 1109/1495 [06:52<02:13,  2.90it/s]
[Running Accuracy]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1109:  74%|█████▉  | 1109/1495 [06:52<02:13,  2.90it/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's the focus in this image?\nA. Medium\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 clarity of this image?
A. Very high
B. Medium
C. Very low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of this image?
A. Very high
B. Medium
C. Very low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. Very high\nB. Medium\nC. Very 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])
 A.

[Running Accuracy]: 0.7818,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1109:  74%|█████▉  | 1110/1495 [06:53<02:11,  2.92it/s]
[Running Accuracy]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1110:  74%|████▍ | 1110/1495 [06:53<02:11,  2.92it/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 clarity of this image?\nA. Very high\nB. Medium\nC. Very 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 flower 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
Is the flower emphasized in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the flower 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([-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]: 0.7811,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1110:  74%|████▍ | 1111/1495 [06:53<02:15,  2.84it/s]
[Running Accuracy]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1111:  74%|██████▋  | 1111/1495 [06:53<02:15,  2.84it/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>Is the flower 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': 'B.<|endoftext|>'} 

prompt A chat between 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([-31.1094], 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]: 0.7813,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1111:  74%|██████▋  | 1112/1495 [06:53<02:13,  2.86it/s]
[Running Accuracy]: 0.7815,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1112:  74%|▋| 1112/1495 [06:53<02:13,  2.86it/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 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': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 sharpness?
A. Clear
B. In focus
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image sharpness?
A. Clear
B. In focus
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How is the image sharpness?\nA. Clear\nB. In focus\nC. 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]: 0.7815,[Response]: C.<|endoftext|>, [Correct Ans]: Very blurry, , [Prog]: 1112:  74%|▋| 1113/1495 [06:54<02:10,  2.93it/s]
[Running Accuracy]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: In focus, , [Prog]: 1113:  74%|██▉ | 1113/1495 [06:54<02:10,  2.93it/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 sharpness?\nA. Clear\nB. In focus\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 prominent color in the image?
A. Red
B. Purple
C. Yellow
D. Brown
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. Purple
C. Yellow
D. Brown
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Red\nB. Purple\nC. Yellow\nD. Brown\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]: 0.7808,[Response]: C.<|endoftext|>, [Correct Ans]: In focus, , [Prog]: 1113:  75%|██▉ | 1114/1495 [06:54<02:08,  2.97it/s]
[Running Accuracy]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1114:  75%|██████▋  | 1114/1495 [06:54<02:08,  2.97it/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>What is the most prominent color in the image?\nA. Red\nB. Purple\nC. Yellow\nD. Brown\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the saturation of the image?
A. Good
B. Poor
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["What is the saturation of the image?\nA. Good\nB. Poor\nC. Average\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.5781], 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]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1114:  75%|██████▋  | 1115/1495 [06:54<02:06,  3.01it/s]
[Running Accuracy]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1115:  75%|█████▉  | 1115/1495 [06:54<02:06,  3.01it/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>What is the 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 distant building in this photo clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the distant building in this photo clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the distant building in this photo clear?\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]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1115:  75%|█████▉  | 1116/1495 [06:55<02:01,  3.13it/s]
[Running Accuracy]: 0.7814,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1116:  75%|███████▍  | 1116/1495 [06:55<02:01,  3.13it/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>Is the distant building in this photo 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 problem occurs in the image?
A. Underexposure
B. Compression artifact
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problem occurs in the image?
A. Underexposure
B. Compression artifact
C. Out of focus
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What problem occurs in the image?\nA. Underexposure\nB. Compression artifact\nC. Out of focus\nD. Motion blur\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]: 0.7814,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1116:  75%|███████▍  | 1117/1495 [06:55<02:00,  3.14it/s]
[Running Accuracy]: 0.7816,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1117:  75%|▋| 1117/1495 [06:55<02:00,  3.14it/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>What problem occurs in the image?\nA. Underexposure\nB. Compression artifact\nC. Out of focus\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>What do you think of the lighting of the left dog face in this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting of the left dog face in this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting of the left dog face in this image?\nA. Bright\nB. Dark\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])
 B.

[Running Accuracy]: 0.7816,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1117:  75%|▋| 1118/1495 [06:55<01:59,  3.17it/s]
[Running Accuracy]: 0.7818,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1118:  75%|█████▉  | 1118/1495 [06:55<01:59,  3.17it/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>What do you think of the lighting of the left dog face in this 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>Is this children's face motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this children's face motion-blurred?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this children's face motion-blurred?\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]: 0.7818,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1118:  75%|█████▉  | 1119/1495 [06:56<01:56,  3.23it/s]
[Running Accuracy]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1119:  75%|██████▋  | 1119/1495 [06:56<01:56,  3.23it/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>Is this children's face motion-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>How is the weather like in this image?
A. Snowy
B. Sunny
C. Foggy
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the weather like in this image?
A. Snowy
B. Sunny
C. Foggy
Answer with the option's letter from the given choices directly.

prompts: [["How is the weather like in this image?\nA. Snowy\nB. Sunny\nC. Foggy\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]: 0.7819,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1119:  75%|██████▋  | 1120/1495 [06:56<01:57,  3.19it/s]
[Running Accuracy]: 0.7821,[Response]: C.<|endoftext|>, [Correct Ans]: Foggy, , [Prog]: 1120:  75%|█████▏ | 1120/1495 [06:56<01:57,  3.19it/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 weather like in this image?\nA. Snowy\nB. Sunny\nC. Foggy\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat 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. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have underexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have underexposure issues?\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]: 0.7821,[Response]: C.<|endoftext|>, [Correct Ans]: Foggy, , [Prog]: 1120:  75%|█████▏ | 1121/1495 [06:56<01:55,  3.23it/s]
[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1121:  75%|██████▋  | 1121/1495 [06:56<01:55,  3.23it/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>Does this picture have underexposure 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>How is the color saturation of the background painting 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 background painting 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 background painting in the image?\nA. Average\nB. Good\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])
 B.

[Running Accuracy]: 0.7823,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1121:  75%|██████▊  | 1122/1495 [06:56<01:55,  3.23it/s]
[Running Accuracy]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1122:  75%|██████  | 1122/1495 [06:56<01:55,  3.23it/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 color saturation of the background painting 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>Does this dog contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this dog contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this dog contain rich texture?\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]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1122:  75%|██████  | 1123/1495 [06:57<01:56,  3.19it/s]
[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1123:  75%|██████▊  | 1123/1495 [06:57<01:56,  3.19it/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>Does this dog 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 the flower part of the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the flower part of the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the flower part of the image clear?\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])
 B.

[Running Accuracy]: 0.7827,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1123:  75%|██████▊  | 1124/1495 [06:57<01:57,  3.15it/s]
[Running Accuracy]: 0.7829,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1124:  75%|██████▊  | 1124/1495 [06:57<01:57,  3.15it/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>Is the flower part 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>What is the darkest object in this picture?
A. Sky
B. Road
C. Building
D. Trees
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. Road
C. Building
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["What is the darkest object in this picture?\nA. Sky\nB. Road\nC. Building\nD. Trees\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]: 0.7829,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1124:  75%|██████▊  | 1125/1495 [06:58<02:32,  2.42it/s]
[Running Accuracy]: 0.7831,[Response]: D.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 1125:  75%|█████▎ | 1125/1495 [06:58<02:32,  2.42it/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>What is the darkest object in this picture?\nA. Sky\nB. Road\nC. Building\nD. Trees\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. 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([-31.0469], 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]: 0.7831,[Response]: D.<|endoftext|>, [Correct Ans]: Trees, , [Prog]: 1125:  75%|█████▎ | 1126/1495 [06:58<02:19,  2.65it/s]
[Running Accuracy]: 0.7833,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1126:  75%|██████▊  | 1126/1495 [06:58<02:19,  2.65it/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 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 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([-30.9219], 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]: 0.7833,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1126:  75%|██████▊  | 1127/1495 [06:58<02:15,  2.71it/s]
[Running Accuracy]: 0.7835,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1127:  75%|██████  | 1127/1495 [06:58<02:15,  2.71it/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 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': 'A.<|endoftext|>'} 

prompt A chat 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 aircraft contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the aircraft contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the aircraft contain rich texture?\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]: 0.7835,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1127:  75%|██████  | 1128/1495 [06:59<02:07,  2.89it/s]
[Running Accuracy]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1128:  75%|███████▌  | 1128/1495 [06:59<02:07,  2.89it/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>Does the aircraft contain rich 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>Are the children in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the children in this picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the children in this picture clear?\nA. Yes\nB. No\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]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1128:  76%|███████▌  | 1129/1495 [06:59<02:33,  2.38it/s]
[Running Accuracy]: 0.7839,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1129:  76%|██████▊  | 1129/1495 [06:59<02:33,  2.38it/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>Are the children 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 kind of visual sensation does the image give?
A. Plain
B. Dark
C. Fresh
D. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual sensation does the image give?
A. Plain
B. Dark
C. Fresh
D. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual sensation does the image give?\nA. Plain\nB. Dark\nC. Fresh\nD. Vibrant\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]: 0.7839,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1129:  76%|██████▊  | 1130/1495 [07:00<02:21,  2.58it/s]
[Running Accuracy]: 0.7841,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1130:  76%|██████  | 1130/1495 [07:00<02:21,  2.58it/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>What kind of visual sensation does the image give?\nA. Plain\nB. Dark\nC. Fresh\nD. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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. Door
B. Blanket
C. Dog
D. Desk lamp
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. Door
B. Blanket
C. Dog
D. Desk lamp
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. Door\nB. Blanket\nC. Dog\nD. Desk lamp\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]: 0.7841,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1130:  76%|██████  | 1131/1495 [07:00<02:12,  2.74it/s]
[Running Accuracy]: 0.7843,[Response]: C.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 1131:  76%|██████▊  | 1131/1495 [07:00<02:12,  2.74it/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>In the composition of the image, which object is emphasized in the center?\nA. Door\nB. Blanket\nC. Dog\nD. Desk 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>Is the advertisement text on the handlebar of this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the advertisement text on the handlebar of this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the advertisement text on the handlebar of this image clear?\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]: 0.7843,[Response]: C.<|endoftext|>, [Correct Ans]: Dog, , [Prog]: 1131:  76%|██████▊  | 1132/1495 [07:00<02:05,  2.88it/s]
[Running Accuracy]: 0.7845,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1132:  76%|██████▊  | 1132/1495 [07:00<02:05,  2.88it/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>Is the advertisement text on the handlebar 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 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]: 0.7845,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1132:  76%|██████▊  | 1133/1495 [07:01<01:59,  3.02it/s]
[Running Accuracy]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1133:  76%|████▌ | 1133/1495 [07:01<01:59,  3.02it/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 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 color 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 color 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 color saturation of this image?\nA. Low\nB. High\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1562], 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]: 0.7846,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1133:  76%|████▌ | 1134/1495 [07:01<01:58,  3.05it/s]
[Running Accuracy]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1134:  76%|████▌ | 1134/1495 [07:01<01:58,  3.05it/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 color saturation 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>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]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1134:  76%|████▌ | 1135/1495 [07:01<01:57,  3.06it/s]
[Running Accuracy]: 0.7841,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1135:  76%|███████▌  | 1135/1495 [07:01<01:57,  3.06it/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>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 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([-31.2812], 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]: 0.7841,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1135:  76%|███████▌  | 1136/1495 [07:02<02:26,  2.44it/s]
[Running Accuracy]: 0.7843,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1136:  76%|██████▊  | 1136/1495 [07:02<02:26,  2.44it/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>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>What distortion is not 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 distortion is not 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 distortion is not 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([-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]: 0.7843,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1136:  76%|██████▊  | 1137/1495 [07:02<02:17,  2.60it/s]
[Running Accuracy]: 0.7836,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1137:  76%|▊| 1137/1495 [07:02<02:17,  2.60it/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>What distortion is not 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': 'C.<|endoftext|>'} 

prompt A chat 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 noise issues with cats?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have noise issues with cats?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have noise issues with cats?\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]: 0.7836,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1137:  76%|▊| 1138/1495 [07:02<02:10,  2.74it/s]
[Running Accuracy]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1138:  76%|██████▊  | 1138/1495 [07:02<02:10,  2.74it/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>Does the image have noise issues with cats?\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 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([-31.1094], 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]: 0.7838,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1138:  76%|██████▊  | 1139/1495 [07:03<02:04,  2.85it/s]
[Running Accuracy]: 0.7840,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1139:  76%|███████▌  | 1139/1495 [07:03<02:04,  2.85it/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>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>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([-31.3281], 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]: 0.7840,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1139:  76%|███████▋  | 1140/1495 [07:03<02:00,  2.95it/s]
[Running Accuracy]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1140:  76%|██████▊  | 1140/1495 [07:03<02:00,  2.95it/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>Is 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>Is the subject clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the subject clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the subject clear in this image?\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]: 0.7842,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1140:  76%|██████▊  | 1141/1495 [07:03<01:57,  3.01it/s]
[Running Accuracy]: 0.7844,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1141:  76%|███████▋  | 1141/1495 [07:03<01:57,  3.01it/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>Is the subject 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 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 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 in the image rich?\nA. Monotonous\nB. Rich\nC. Moderate\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], 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]: 0.7844,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1141:  76%|███████▋  | 1142/1495 [07:04<01:55,  3.06it/s]
[Running Accuracy]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1142:  76%|█▌| 1142/1495 [07:04<01:55,  3.06it/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>Is the color 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>What is the overall feeling conveyed by the image?
A. Cheerful
B. Gloomy
C. Annoying
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the overall feeling conveyed by the image?
A. Cheerful
B. Gloomy
C. Annoying
Answer with the option's letter from the given choices directly.

prompts: [["What is the overall feeling conveyed by the image?\nA. Cheerful\nB. Gloomy\nC. Annoying\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]: 0.7837,[Response]: B.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1142:  76%|█▌| 1143/1495 [07:04<01:55,  3.03it/s]
[Running Accuracy]: 0.7839,[Response]: A.<|endoftext|>, [Correct Ans]: Cheerful, , [Prog]: 1143:  76%|███ | 1143/1495 [07:04<01:55,  3.03it/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>What is the overall feeling conveyed by the image?\nA. Cheerful\nB. Gloomy\nC. Annoying\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the ground contain rich 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]: 0.7839,[Response]: A.<|endoftext|>, [Correct Ans]: Cheerful, , [Prog]: 1143:  77%|███ | 1144/1495 [07:05<02:26,  2.39it/s]
[Running Accuracy]: 0.7841,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1144:  77%|██████▉  | 1144/1495 [07:05<02:26,  2.39it/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>Does 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>Is the image overexposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image overexposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the image overexposed?\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]: 0.7841,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1144:  77%|██████▉  | 1145/1495 [07:05<02:14,  2.60it/s]
[Running Accuracy]: 0.7843,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1145:  77%|██████▉  | 1145/1495 [07:05<02:14,  2.60it/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>Is the 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 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([-31.0625], 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]: 0.7843,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1145:  77%|██████▉  | 1146/1495 [07:05<02:05,  2.77it/s]
[Running Accuracy]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1146:  77%|██████▉  | 1146/1495 [07:05<02:05,  2.77it/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>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': 'B.<|endoftext|>'} 

prompt A chat 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 plants in the bottom of this image contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the plants in the bottom of this image contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Do the plants in the bottom of this image contain rich texture?\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]: 0.7836,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1146:  77%|██████▉  | 1147/1495 [07:06<02:28,  2.34it/s]
[Running Accuracy]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1147:  77%|██████▉  | 1147/1495 [07:06<02:28,  2.34it/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>Do the plants in the bottom of this image contain rich 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>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.], device='cuda:0', dtype=torch.float16)
Attn torch.Size([1, 729, 32])
vlm_prompt torch.Size([1, 729, 1152])
vlm_emd torch.Size([1, 729, 1152])
all_hidden_state shape: torch.Size([1, 729, 1152])
 A.

[Running Accuracy]: 0.7838,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1147:  77%|██████▉  | 1148/1495 [07:06<02:18,  2.51it/s]
[Running Accuracy]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1148:  77%|██████▏ | 1148/1495 [07:06<02:18,  2.51it/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 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>How is the lighting of the image?
A. Dim and Gloomy
B. Bright and Cheerful
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of the image?
A. Dim and Gloomy
B. Bright and Cheerful
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of the image?\nA. Dim and Gloomy\nB. Bright and Cheerful\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]: 0.7840,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1148:  77%|██████▏ | 1149/1495 [07:07<02:28,  2.33it/s]
[Running Accuracy]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Bright and Cheerful, , [Prog]: 1149:  77%|▊| 1149/1495 [07:07<02:28,  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 of the image?\nA. Dim and Gloomy\nB. Bright and 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>Is this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image colorful?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image 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]: 0.7833,[Response]: A.<|endoftext|>, [Correct Ans]: Bright and Cheerful, , [Prog]: 1149:  77%|▊| 1150/1495 [07:07<02:16,  2
[Running Accuracy]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1150:  77%|███████▋  | 1150/1495 [07:07<02:16,  2.53it/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>Is 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>How is the level of exposure in the image?
A. Underexposed
B. Overexposed
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the level of exposure in the image?
A. Underexposed
B. Overexposed
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the level of exposure in the image?\nA. Underexposed\nB. Overexposed\nC. Moderate\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]: 0.7835,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1150:  77%|███████▋  | 1151/1495 [07:07<02:09,  2.66it/s]
[Running Accuracy]: 0.7837,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1151:  77%|███ | 1151/1495 [07:07<02:09,  2.66it/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 level of exposure in the image?\nA. Underexposed\nB. Overexposed\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>How is the saturation of the burger on the right side 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 saturation of the burger on the right side of the image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of the burger on the right side of the 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])
 B.

[Running Accuracy]: 0.7837,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1151:  77%|███ | 1152/1495 [07:08<02:03,  2.78it/s]
[Running Accuracy]: 0.7830,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1152:  77%|██████▉  | 1152/1495 [07:08<02:03,  2.78it/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 saturation of the burger on the right side 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>How is the image clarity?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\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]: 0.7830,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1152:  77%|██████▉  | 1153/1495 [07:08<01:58,  2.88it/s]
[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1153:  77%|██████▏ | 1153/1495 [07:08<01:58,  2.88it/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?\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>What issues are present in this image?
A. Overexposure
B. Compression Artifacts
C. Underexposure
D. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What issues are present in this image?
A. Overexposure
B. Compression Artifacts
C. Underexposure
D. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What issues are present in this image?\nA. Overexposure\nB. Compression Artifacts\nC. Underexposure\nD. 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])
 B.

[Running Accuracy]: 0.7832,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1153:  77%|██████▏ | 1154/1495 [07:08<01:53,  2.99it/s]
[Running Accuracy]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1154:  77%|▊| 1154/1495 [07:08<01:53,  2.99it/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>What issues are present in this image?\nA. Overexposure\nB. Compression Artifacts\nC. Underexposure\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>How is the color vibrance of the image?
A. Totally Black and White
B. Plain
C. Very Vivid
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color vibrance of the image?
A. Totally Black and White
B. Plain
C. Very Vivid
Answer with the option's letter from the given choices directly.

prompts: [["How is the color vibrance of the image?\nA. Totally Black and White\nB. Plain\nC. Very Vivid\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.9219], 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]: 0.7825,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1154:  77%|▊| 1155/1495 [07:09<01:56,  2.92it/s
[Running Accuracy]: 0.7818,[Response]: A.<|endoftext|>, [Correct Ans]: Plain, , [Prog]: 1155:  77%|█████▍ | 1155/1495 [07:09<01:56,  2.92it/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 color vibrance of the image?\nA. Totally Black and White\nB. Plain\nC. Very 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>In the composition of this image, is the man being 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
In the composition of this image, is the man being emphasized in the center of the composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["In the composition of this image, is the man being 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([-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]: 0.7818,[Response]: A.<|endoftext|>, [Correct Ans]: Plain, , [Prog]: 1155:  77%|█████▍ | 1156/1495 [07:09<01:53,  2.98it/s]
[Running Accuracy]: 0.7820,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1156:  77%|██████▉  | 1156/1495 [07:09<01:53,  2.98it/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>In the composition of this image, is the man being 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>Is the coin in the image totally clear, partly clear, or totally blurred?
A. Partly clear
B. Totally blurred
C. Totally clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the coin in the image totally clear, partly clear, or totally blurred?
A. Partly clear
B. Totally blurred
C. Totally clear
Answer with the option's letter from the given choices directly.

prompts: [["Is the coin in the image totally clear, partly clear, or totally blurred?\nA. Partly clear\nB. Totally blurred\nC. Totally clear\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]: 0.7820,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1156:  77%|██████▉  | 1157/1495 [07:09<01:52,  2.99it/s]
[Running Accuracy]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Partly clear, , [Prog]: 1157:  77%|▊| 1157/1495 [07:09<01:52,  2.99it/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>Is the coin in the image totally clear, partly clear, or totally blurred?\nA. Partly clear\nB. Totally blurred\nC. Totally 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>How would you rate 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
How would you rate 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: [["How would you rate 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([-31.4531], 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]: 0.7822,[Response]: A.<|endoftext|>, [Correct Ans]: Partly clear, , [Prog]: 1157:  77%|▊| 1158/1495 [07:10<01:50,  3.04it/s
[Running Accuracy]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1158:  77%|██████▏ | 1158/1495 [07:10<01:50,  3.04it/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 would you rate 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': 'B.<|endoftext|>'} 

prompt A chat between 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 grass in the image?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the grass in the image?
A. Slight
B. Moderate
C. Severe
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the grass in the image?\nA. Slight\nB. Moderate\nC. Severe\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]: 0.7815,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1158:  78%|██████▏ | 1159/1495 [07:10<01:49,  3.07it/s]
[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1159:  78%|████▋ | 1159/1495 [07:10<01:49,  3.07it/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 blurry is the grass in the image?\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>How clear is the forest in the image?
A. Poor
B. Medium
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the forest in the image?
A. Poor
B. Medium
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the forest in the image?\nA. Poor\nB. Medium\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])
 A.

[Running Accuracy]: 0.7808,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1159:  78%|████▋ | 1160/1495 [07:10<01:49,  3.06it/s]
[Running Accuracy]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1160:  78%|██████▏ | 1160/1495 [07:10<01:49,  3.06it/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 clear is the forest in the image?\nA. Poor\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>What is the worst distortion in this picture?
A. Out of focus
B. Compression
C. Noise
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. Out of focus
B. Compression
C. Noise
D. Brightness
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. Compression\nC. Noise\nD. Brightness\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]: 0.7810,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1160:  78%|██████▏ | 1161/1495 [07:11<02:24,  2.32it/s]
[Running Accuracy]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1161:  78%|▊| 1161/1495 [07:11<02:24,  2.32it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Compression\nC. Noise\nD. Brightness\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 details of the fur look real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the details of the fur look real?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the details of the fur look real?\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]: 0.7812,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1161:  78%|▊| 1162/1495 [07:11<02:13,  2.49it/s
[Running Accuracy]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1162:  78%|███████▊  | 1162/1495 [07:11<02:13,  2.49it/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>Does the details of the fur look real?\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 the yellow flower 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 yellow flower 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 yellow flower in the image?\nA. Blurry\nB. Moderate\nC. Clear\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]: 0.7806,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1162:  78%|███████▊  | 1163/1495 [07:12<02:06,  2.63it/s]
[Running Accuracy]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1163:  78%|████▋ | 1163/1495 [07:12<02:06,  2.63it/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 clear is the yellow flower in the image?\nA. Blurry\nB. Moderate\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>Which color is the brightest in this image?
A. Gray
B. Light blue
C. Dark blue
D. Yellow
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which color is the brightest in this image?
A. Gray
B. Light blue
C. Dark blue
D. Yellow
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the brightest in this image?\nA. Gray\nB. Light blue\nC. Dark blue\nD. Yellow\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]: 0.7799,[Response]: B.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1163:  78%|████▋ | 1164/1495 [07:12<02:01,  2.73it/s]
[Running Accuracy]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Dark blue, , [Prog]: 1164:  78%|██▎| 1164/1495 [07:12<02:01,  2.73it/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>Which color is the brightest in this image?\nA. Gray\nB. Light blue\nC. Dark blue\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 most apparent distortion of the human in this image?
A. Motion 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 of the human in this image?
A. Motion blur
B. Over-exposure
C. Noise
Answer with the option's letter from the given choices directly.

prompts: [["What is the most apparent distortion of the human in this image?\nA. Motion blur\nB. Over-exposure\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]: 0.7792,[Response]: A.<|endoftext|>, [Correct Ans]: Dark blue, , [Prog]: 1164:  78%|██▎| 1165/1495 [07:12<01:56,  2.84it/s]
[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1165:  78%|▊| 1165/1495 [07:12<01:56,  2.84it/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>What is the most apparent distortion of the human in this image?\nA. Motion blur\nB. Over-exposure\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 people of this picture out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people of this picture out of focus?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the people of this picture out of focus?\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]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1165:  78%|▊| 1166/1495 [07:13<02:22,  2.31it/s]
[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1166:  78%|███████  | 1166/1495 [07:13<02:22,  2.31it/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>Are the people of this picture 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 these noise on the wall?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is these noise on the wall?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is these noise on the wall?\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]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1166:  78%|███████  | 1167/1495 [07:13<02:29,  2.20it/s]
[Running Accuracy]: 0.7798,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1167:  78%|███████  | 1167/1495 [07:13<02:29,  2.20it/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>Is these noise on the wall?\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 good composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have good composition?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have good composition?\nA. Yes\nB. No\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]: 0.7798,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1167:  78%|███████  | 1168/1495 [07:14<02:17,  2.38it/s]
[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1168:  78%|███████  | 1168/1495 [07:14<02:17,  2.38it/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>Does this image have good 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 cup out of focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cup out of focus in this picture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cup out of focus 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])
 A.

[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1168:  78%|███████  | 1169/1495 [07:14<02:06,  2.57it/s]
[Running Accuracy]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1169:  78%|███████▊  | 1169/1495 [07:14<02:06,  2.57it/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>Is the cup out of focus 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>Is this image very clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image very clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image very clear?\nA. Yes\nB. No\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]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1169:  78%|███████▊  | 1170/1495 [07:14<01:59,  2.73it/s]
[Running Accuracy]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1170:  78%|███████▊  | 1170/1495 [07:14<01:59,  2.73it/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>Is this image 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>Which object in the image is the focus?
A. Car
B. Person
C. Signboard
D. Building
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the focus?
A. Car
B. Person
C. Signboard
D. Building
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the focus?\nA. Car\nB. Person\nC. Signboard\nD. Building\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]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1170:  78%|███████▊  | 1171/1495 [07:15<01:54,  2.83it/s]
[Running Accuracy]: 0.7797,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1171:  78%|████▋ | 1171/1495 [07:15<01:54,  2.83it/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>Which object in the image is the focus?\nA. Car\nB. Person\nC. Signboard\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>What is the main distortion in the image?
A. Compression artifacts
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 main distortion in the image?
A. Compression artifacts
B. Underexposure
C. Out of focus
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion in the image?\nA. Compression artifacts\nB. Underexposure\nC. Out of focus\nD. Overexposure\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]: 0.7797,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1171:  78%|████▋ | 1172/1495 [07:15<01:50,  2.93it/s]
[Running Accuracy]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1172:  78%|▊| 1172/1495 [07:15<01:50,  2.93it/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>What is the main distortion in the image?\nA. Compression artifacts\nB. Underexposure\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>Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise?\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]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1172:  78%|▊| 1173/1495 [07:15<01:47,  2.99it/s
[Running Accuracy]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1173:  78%|███████  | 1173/1495 [07:15<01:47,  2.99it/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>Does this picture 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>What is the color saturation of the bus 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 bus 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 bus in the image?\nA. Low\nB. Moderate\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]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1173:  79%|███████  | 1174/1495 [07:16<01:47,  3.00it/s]
[Running Accuracy]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1174:  79%|███▏| 1174/1495 [07:16<01:47,  3.00it/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>What is the color saturation of the bus in the image?\nA. Low\nB. Moderate\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>Does this image provide a bright visual experience?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image provide a bright visual experience?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image provide a bright visual experience?\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]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1174:  79%|███▏| 1175/1495 [07:16<01:46,  3.01it/s]
[Running Accuracy]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1175:  79%|███████▊  | 1175/1495 [07:16<01:46,  3.01it/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>Does this image provide a bright 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>How is the color in this image?
A. Vivid
B. Average
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color in this image?
A. Vivid
B. Average
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color in this image?\nA. Vivid\nB. Average\nC. Monotonous\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]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1175:  79%|███████▊  | 1176/1495 [07:16<01:43,  3.08it/s]
[Running Accuracy]: 0.7789,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1176:  79%|█▌| 1176/1495 [07:16<01:43,  3.08it/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 color in this image?\nA. Vivid\nB. Average\nC. Monotonous\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Overexposure
C. Out of focus
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. Overexposure
C. Out of focus
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. Overexposure\nC. Out of focus\nD. Underexposure\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])
 D.

[Running Accuracy]: 0.7789,[Response]: C.<|endoftext|>, [Correct Ans]: Monotonous, , [Prog]: 1176:  79%|█▌| 1177/1495 [07:17<01:42,  3.11it/s]
[Running Accuracy]: 0.7791,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1177:  79%|▊| 1177/1495 [07:17<01:42,  3.11it/
 {'prompt': "A chat between 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. Overexposure\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>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([-31.4688], 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]: 0.7791,[Response]: D.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1177:  79%|▊| 1178/1495 [07:17<01:46,  2.97it/
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1178:  79%|███████  | 1178/1495 [07:17<01:46,  2.97it/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>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 is not a primary color tone in the image?
A. White
B. Red
C. Green
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following is not a primary color tone in the image?
A. White
B. Red
C. Green
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following is not a primary color tone in the image?\nA. White\nB. Red\nC. Green\nD. Blue\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]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1178:  79%|███████  | 1179/1495 [07:17<01:45,  2.99it/s]
[Running Accuracy]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1179:  79%|███████  | 1179/1495 [07:17<01:45,  2.99it/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>Which of the following is not a primary color tone in the image?\nA. White\nB. Red\nC. Green\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>What kind of feeling does this image give?
A. Happy
B. Vibrant
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does this image give?
A. Happy
B. Vibrant
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does this image give?\nA. Happy\nB. Vibrant\nC. Dark\nD. Fresh\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])
 C.

[Running Accuracy]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1179:  79%|███████  | 1180/1495 [07:18<01:43,  3.03it/s]
[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1180:  79%|██████▎ | 1180/1495 [07:18<01:43,  3.03it/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>What kind of feeling does this image give?\nA. Happy\nB. Vibrant\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>Are the cars blurry in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the cars blurry in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the cars blurry in this image?\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]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1180:  79%|██████▎ | 1181/1495 [07:18<01:43,  3.03it/s]
[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1181:  79%|███████  | 1181/1495 [07:18<01:43,  3.03it/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>Are the cars blurry 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 saturation of the street lamp in the picture?
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 street lamp in the picture?
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 street lamp in the picture?\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])
 B.

[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1181:  79%|███████  | 1182/1495 [07:18<01:42,  3.05it/s]
[Running Accuracy]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1182:  79%|██████▎ | 1182/1495 [07:18<01:42,  3.05it/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 color saturation of the street lamp in the picture?\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 are the lighting conditions of the smartphone in the image?
A. Moderate
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What are the lighting conditions of the smartphone in the image?
A. Moderate
B. Bright
C. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What are the lighting conditions of the smartphone in the image?\nA. Moderate\nB. Bright\nC. Dark\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]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1182:  79%|██████▎ | 1183/1495 [07:19<01:41,  3.06it/s]
[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1183:  79%|██████▎ | 1183/1495 [07:19<01:41,  3.06it/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>What are the lighting conditions of the smartphone in the image?\nA. Moderate\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>What is the brightest part in this image?
A. Soup
B. Bowl
C. Noodles
D. Meat
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this image?
A. Soup
B. Bowl
C. Noodles
D. Meat
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this image?\nA. Soup\nB. Bowl\nC. Noodles\nD. Meat\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])
 C.

[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1183:  79%|██████▎ | 1184/1495 [07:19<01:41,  3.05it/s]
[Running Accuracy]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Noodles, , [Prog]: 1184:  79%|███▉ | 1184/1495 [07:19<01:41,  3.05it/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>What is the brightest part in this image?\nA. Soup\nB. Bowl\nC. Noodles\nD. Meat\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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([-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]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Noodles, , [Prog]: 1184:  79%|███▉ | 1185/1495 [07:19<01:38,  3.14it/s]
[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1185:  79%|███████▉  | 1185/1495 [07:19<01:38,  3.14it/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>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 of the following quality issues does this image not have?
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 quality issues does this image not have?
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 quality issues does this image not have?\nA. Overexposure\nB. Out of focus\nC. Noise\nD. Underexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.3281], 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])
 D.

[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1185:  79%|███████▉  | 1186/1495 [07:20<01:38,  3.14it/s]
[Running Accuracy]: 0.7782,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1186:  79%|▊| 1186/1495 [07:20<01:38,  3.14it/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>Which of the following quality issues does this image not have?\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 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])
 A.

[Running Accuracy]: 0.7782,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1186:  79%|▊| 1187/1495 [07:20<01:41,  3.04it/s
[Running Accuracy]: 0.7784,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1187:  79%|████▊ | 1187/1495 [07:20<01:41,  3.04it/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 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 arrangement of elements in this image?
A. Bad
B. Good
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. Bad
B. Good
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the arrangement of elements in this image?\nA. Bad\nB. Good\nC. Acceptable\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]: 0.7784,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1187:  79%|████▊ | 1188/1495 [07:20<01:42,  2.99it/s]
[Running Accuracy]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1188:  79%|██████▎ | 1188/1495 [07:20<01:42,  2.99it/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 arrangement of elements in this image?\nA. Bad\nB. Good\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>Which object is emphasized in the composition of the image?
A. Shelf
B. Woman and baby
C. Sofa
D. Cabinet
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. Shelf
B. Woman and baby
C. Sofa
D. Cabinet
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Shelf\nB. Woman and baby\nC. Sofa\nD. Cabinet\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]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1188:  80%|██████▎ | 1189/1495 [07:21<01:40,  3.03it/s]
[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Woman and baby, , [Prog]: 1189:  80%|▊| 1189/1495 [07:21<01:40,  3.03it
 {'prompt': "A chat between 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. Shelf\nB. Woman and baby\nC. Sofa\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 color of the entertainment facilities 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 entertainment facilities 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 entertainment facilities in this image vibrant?\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]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Woman and baby, , [Prog]: 1189:  80%|▊| 1190/1495 [07:21<01:40,  3.03it
[Running Accuracy]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1190:  80%|███████▏ | 1190/1495 [07:21<01:40,  3.03it/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>Is the color of the entertainment facilities 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 saturation 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 saturation of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the saturation of this image?\nA. High\nB. Medium\nC. Low\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]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1190:  80%|███████▏ | 1191/1495 [07:21<01:41,  3.00it/s]
[Running Accuracy]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1191:  80%|███████▏ | 1191/1495 [07:21<01:41,  3.00it/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 saturation 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>How is the overall 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 overall 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 overall 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([-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]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1191:  80%|███████▏ | 1192/1495 [07:22<01:41,  3.00it/s]
[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1192:  80%|██████▍ | 1192/1495 [07:22<01:41,  3.00it/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 overall 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>Which object is the focus of this image?
A. Plant
B. Car
C. Girl
D. Pillar
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus of this image?
A. Plant
B. Car
C. Girl
D. Pillar
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus of this image?\nA. Plant\nB. Car\nC. Girl\nD. Pillar\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]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1192:  80%|██████▍ | 1193/1495 [07:22<01:39,  3.04it/s]
[Running Accuracy]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1193:  80%|██████▍ | 1193/1495 [07:22<01:39,  3.04it/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>Which object is the focus of this image?\nA. Plant\nB. Car\nC. Girl\nD. Pillar\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image pyramid-shaped?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image pyramid-shaped?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.8438], 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]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1193:  80%|██████▍ | 1194/1495 [07:22<01:45,  2.85it/s]
[Running Accuracy]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1194:  80%|███████▉  | 1194/1495 [07:22<01:45,  2.85it/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>Is the composition of this image pyramid-shaped?\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 colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image colorful?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image colorful?\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]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1194:  80%|███████▉  | 1195/1495 [07:23<01:45,  2.84it/s]
[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1195:  80%|███████▉  | 1195/1495 [07:23<01:45,  2.84it/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>Is this image 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 man walking in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man walking in this image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the man walking in this image 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])
 B.

[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1195:  80%|████████  | 1196/1495 [07:23<01:45,  2.85it/s]
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1196:  80%|████████  | 1196/1495 [07:23<01:45,  2.85it/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>Is the man walking 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>How would you rate the clarity of this image?
A. High
B. Medium
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. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of this image?\nA. High\nB. Medium\nC. Low\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]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1196:  80%|████████  | 1197/1495 [07:24<02:05,  2.38it/s]
[Running Accuracy]: 0.7786,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1197:  80%|███████▏ | 1197/1495 [07:24<02:05,  2.38it/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 would you rate the 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>Is the lighting good in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the lighting good in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting good in this image?\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]: 0.7786,[Response]: C.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1197:  80%|███████▏ | 1198/1495 [07:24<02:21,  2.10it/s]
[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1198:  80%|███████▏ | 1198/1495 [07:24<02:21,  2.10it/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>Is the lighting good 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 people in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in the image clear?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in the image 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])
 B.

[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1198:  80%|███████▏ | 1199/1495 [07:24<02:08,  2.30it/s]
[Running Accuracy]: 0.7781,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1199:  80%|████████  | 1199/1495 [07:24<02:08,  2.30it/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>Are the people 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>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([-31.3906], 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]: 0.7781,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1199:  80%|████████  | 1200/1495 [07:25<01:58,  2.50it/s]
[Running Accuracy]: 0.7783,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1200:  80%|███████▏ | 1200/1495 [07:25<01:58,  2.50it/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>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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. 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. Motion blur
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. Motion blur\nB. Overexposure\nC. Noise\nD. Underexposure\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]: 0.7783,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1200:  80%|███████▏ | 1201/1495 [07:25<02:12,  2.21it/s]
[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1201:  80%|▊| 1201/1495 [07:25<02:12,  2.21it/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>What is 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>How is the brightness of the building 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 brightness of the building in the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the brightness of the building in the image?\nA. High\nB. Low\nC. Medium\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]: A.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1201:  80%|▊| 1202/1495 [07:26<02:24,  2.02it/s]
[Running Accuracy]: 0.7787,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1202:  80%|███████▏ | 1202/1495 [07:26<02:24,  2.02it/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 brightness of the building in the 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>Is the dog on the right side of the image the sharpest object?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dog on the right side of the image the sharpest object?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog on the right side of the image the sharpest object?\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]: 0.7787,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1202:  80%|███████▏ | 1203/1495 [07:26<02:09,  2.25it/s]
[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1203:  80%|███████▏ | 1203/1495 [07:26<02:09,  2.25it/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>Is the dog on the right side of the image the sharpest object?\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([-31.3281], 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]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1203:  81%|███████▏ | 1204/1495 [07:27<01:59,  2.44it/s]
[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1204:  81%|███████▏ | 1204/1495 [07:27<01:59,  2.44it/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>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>From which direction does the light of the image come from?
A. Below
B. Front
C. Side
D. Above
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light of the image come from?
A. Below
B. Front
C. Side
D. Above
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light of the image come from?\nA. Below\nB. Front\nC. Side\nD. Above\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]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1204:  81%|███████▎ | 1205/1495 [07:27<01:51,  2.59it/s]
[Running Accuracy]: 0.7784,[Response]: D.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 1205:  81%|█████▋ | 1205/1495 [07:27<01:51,  2.59it/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>From which direction does the light of the image come from?\nA. Below\nB. Front\nC. Side\nD. Above\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>In image composition, which object is emphasized in the center of the scene?
A. Car
B. Girl
C. Pillow
D. Chair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
In image composition, which object is emphasized in the center of the scene?
A. Car
B. Girl
C. Pillow
D. Chair
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center of the scene?\nA. Car\nB. Girl\nC. Pillow\nD. Chair\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]: 0.7784,[Response]: D.<|endoftext|>, [Correct Ans]: Front, , [Prog]: 1205:  81%|█████▋ | 1206/1495 [07:27<01:45,  2.74it/s]
[Running Accuracy]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1206:  81%|██████▍ | 1206/1495 [07:27<01:45,  2.74it/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>In image composition, which object is emphasized in the center of the scene?\nA. Car\nB. Girl\nC. Pillow\nD. Chair\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. 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 human 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 human in this 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])
 C.

[Running Accuracy]: 0.7786,[Response]: B.<|endoftext|>, [Correct Ans]: Girl, , [Prog]: 1206:  81%|██████▍ | 1207/1495 [07:28<01:41,  2.84it/s]
[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1207:  81%|██████▍ | 1207/1495 [07:28<01:41,  2.84it/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 lighting of the human in 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>Is the bike in this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the bike in this picture in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the bike in this picture in focus?\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]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1207:  81%|██████▍ | 1208/1495 [07:28<02:01,  2.36it/s]
[Running Accuracy]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1208:  81%|████████  | 1208/1495 [07:28<02:01,  2.36it/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>Is the bike in this picture 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>Which object is emphasized in the composition of the image?
A. Puzzle piece
B. Chair
C. Cat
D. Puzzle hint image
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. Puzzle piece
B. Chair
C. Cat
D. Puzzle hint image
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Puzzle piece\nB. Chair\nC. Cat\nD. Puzzle hint image\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]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1208:  81%|████████  | 1209/1495 [07:28<01:51,  2.56it/s]
[Running Accuracy]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 1209:  81%|███████▎ | 1209/1495 [07:29<01:51,  2.56it/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>Which object is emphasized in the composition of the image?\nA. Puzzle piece\nB. Chair\nC. Cat\nD. Puzzle hint image\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 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 motion blur 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 motion blur in this picture?\nA. Severe\nB. Moderate\nC. Mild\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])
 A.

[Running Accuracy]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Cat, , [Prog]: 1209:  81%|███████▎ | 1210/1495 [07:29<01:44,  2.72it/s]
[Running Accuracy]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1210:  81%|████▊ | 1210/1495 [07:29<01:44,  2.72it/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 severe is the motion blur 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>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([-30.9844], 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]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1210:  81%|████▊ | 1211/1495 [07:29<01:39,  2.85it/s]
[Running Accuracy]: 0.7795,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1211:  81%|██████▍ | 1211/1495 [07:29<01:39,  2.85it/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 colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What has the highest saturation in the image?
A. Grass
B. Dog
C. Reference standard
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What has the highest saturation in the image?
A. Grass
B. Dog
C. Reference standard
Answer with the option's letter from the given choices directly.

prompts: [["What has the highest saturation in the image?\nA. Grass\nB. Dog\nC. Reference standard\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]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1211:  81%|██████▍ | 1212/1495 [07:29<01:37,  2.90it/s]
[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: Reference standard, , [Prog]: 1212:  81%|▊| 1212/1495 [07:29<01:37,  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 has the highest saturation in the image?\nA. Grass\nB. Dog\nC. Reference standard\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 darkness?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image give a sense of darkness?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a sense of darkness?\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]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: Reference standard, , [Prog]: 1212:  81%|▊| 1213/1495 [07:30<01:35,  2.
[Running Accuracy]: 0.7791,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1213:  81%|███████▎ | 1213/1495 [07:30<01:35,  2.94it/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>Does this image give a sense of darkness?\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 there too many miscellaneous colors in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there too many miscellaneous colors in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are there too many miscellaneous colors in the 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]: 0.7791,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1213:  81%|███████▎ | 1214/1495 [07:30<01:33,  3.01it/s]
[Running Accuracy]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1214:  81%|███████▎ | 1214/1495 [07:30<01:33,  3.01it/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>Are there too many miscellaneous colors 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 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([-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]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1214:  81%|███████▎ | 1215/1495 [07:30<01:32,  3.02it/s]
[Running Accuracy]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1215:  81%|███████▎ | 1215/1495 [07:30<01:32,  3.02it/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>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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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([-31.2188], 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]: 0.7794,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1215:  81%|███████▎ | 1216/1495 [07:31<01:32,  3.01it/s]
[Running Accuracy]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1216:  81%|████▉ | 1216/1495 [07:31<01:32,  3.01it/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 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 the beverage the focus in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the beverage the focus in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the beverage the focus in this image?\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]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1216:  81%|████▉ | 1217/1495 [07:31<01:32,  3.01it/s]
[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1217:  81%|███████▎ | 1217/1495 [07:31<01:32,  3.01it/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>Is the beverage the focus 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 overall lighting condition of the image?
A. Too dark
B. Too bright
C. Just fine
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the overall lighting condition of the image?
A. Too dark
B. Too bright
C. Just fine
Answer with the option's letter from the given choices directly.

prompts: [["How is the overall lighting condition of the image?\nA. Too dark\nB. Too bright\nC. Just fine\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]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1217:  81%|███████▎ | 1218/1495 [07:31<01:30,  3.07it/s]
[Running Accuracy]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 1218:  81%|██▍| 1218/1495 [07:31<01:30,  3.07it/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 overall lighting condition of the image?\nA. Too dark\nB. Too bright\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>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([-30.9531], 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]: 0.7791,[Response]: C.<|endoftext|>, [Correct Ans]: Just fine, , [Prog]: 1218:  82%|██▍| 1219/1495 [07:32<01:27,  3.15it/s]
[Running Accuracy]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1219:  82%|███████▎ | 1219/1495 [07:32<01:27,  3.15it/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>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>What is the worst distortion in this picture?
A. Underexposure
B. Noise
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. Noise
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. Noise\nC. Out of focus\nD. Motion blur\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]: 0.7793,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1219:  82%|███████▎ | 1220/1495 [07:32<01:29,  3.08it/s]
[Running Accuracy]: 0.7795,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1220:  82%|▊| 1220/1495 [07:32<01:29,  3.08it/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>What is the worst distortion in this picture?\nA. Underexposure\nB. Noise\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>Are the people in the picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the people in the picture clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the people in the picture clear?\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])
 B.

[Running Accuracy]: 0.7795,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1220:  82%|▊| 1221/1495 [07:33<01:48,  2.53it/s
[Running Accuracy]: 0.7797,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1221:  82%|████████▏ | 1221/1495 [07:33<01:48,  2.53it/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>Are the people in the 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>Which object is emphasized in the center of the composition of this image?
A. Flower bed
B. Ground
C. Building
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center of the composition of this image?
A. Flower bed
B. Ground
C. Building
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of the composition of this image?\nA. Flower bed\nB. Ground\nC. Building\nD. Trees\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]: 0.7797,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1221:  82%|████████▏ | 1222/1495 [07:33<01:41,  2.69it/s]
[Running Accuracy]: 0.7799,[Response]: A.<|endoftext|>, [Correct Ans]: Flower bed, , [Prog]: 1222:  82%|█▋| 1222/1495 [07:33<01:41,  2.69it/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>Which object is emphasized in the center of the composition of this image?\nA. Flower bed\nB. Ground\nC. Building\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 is the worst distortion in this picture?
A. Sharpness
B. Underexposure
C. Motion blur
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. Sharpness
B. Underexposure
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this picture?\nA. Sharpness\nB. Underexposure\nC. Motion blur\nD. Overexposure\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]: 0.7799,[Response]: A.<|endoftext|>, [Correct Ans]: Flower bed, , [Prog]: 1222:  82%|█▋| 1223/1495 [07:34<01:59,  2.29it/s]
[Running Accuracy]: 0.7800,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1223:  82%|▊| 1223/1495 [07:34<01:59,  2.29it/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>What is the worst distortion in this picture?\nA. Sharpness\nB. Underexposure\nC. Motion blur\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>How severe is the over-exposure problem in this image?
A. Not severe
B. Very severe
C. Moderately severe
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is the over-exposure problem in this image?
A. Not severe
B. Very severe
C. Moderately severe
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the over-exposure problem in this image?\nA. Not severe\nB. Very severe\nC. Moderately severe\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]: 0.7800,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1223:  82%|▊| 1224/1495 [07:34<01:49,  2.47it/s
[Running Accuracy]: 0.7802,[Response]: B.<|endoftext|>, [Correct Ans]: Very severe, , [Prog]: 1224:  82%|▊| 1224/1495 [07:34<01:49,  2.47it/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 severe is the over-exposure problem in this image?\nA. Not severe\nB. Very severe\nC. Moderately severe\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 person on the cliff in this image blurry?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
To what extent is the person on the cliff in this image blurry?
A. Slight
B. Severe
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["To what extent is the person on the cliff in this image blurry?\nA. Slight\nB. Severe\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]: 0.7802,[Response]: B.<|endoftext|>, [Correct Ans]: Very severe, , [Prog]: 1224:  82%|▊| 1225/1495 [07:34<01:46,  2.53it/s]
[Running Accuracy]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1225:  82%|████▉ | 1225/1495 [07:34<01:46,  2.53it/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>To what extent is the person on the cliff in this image blurry?\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>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([-31.0781], 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]: 0.7796,[Response]: A.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1225:  82%|████▉ | 1226/1495 [07:35<01:42,  2.61it/s]
[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1226:  82%|████▉ | 1226/1495 [07:35<01:42,  2.61it/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 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>Does this image feature any repeated elements?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image feature any repeated elements?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image feature any repeated elements?\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]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1226:  82%|████▉ | 1227/1495 [07:35<01:38,  2.73it/s]
[Running Accuracy]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1227:  82%|███████▍ | 1227/1495 [07:35<01:38,  2.73it/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>Does this image feature any repeated elements?\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. 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([-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]: 0.7791,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1227:  82%|███████▍ | 1228/1495 [07:35<01:35,  2.79it/s]
[Running Accuracy]: 0.7793,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1228:  82%|██████▌ | 1228/1495 [07:35<01:35,  2.79it/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 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': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 relatively large green plant in the middle of this image?
A. Moderate
B. Vivid green
C. Monotonous
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the relatively large green plant in the middle of this image?
A. Moderate
B. Vivid green
C. Monotonous
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the relatively large green plant in the middle of this image?\nA. Moderate\nB. Vivid green\nC. Monotonous\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]: 0.7793,[Response]: B.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1228:  82%|██████▌ | 1229/1495 [07:36<01:34,  2.80it/s]
[Running Accuracy]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: Vivid green, , [Prog]: 1229:  82%|▊| 1229/1495 [07:36<01:34,  2.80it/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 color of the relatively large green plant in the middle of this image?\nA. Moderate\nB. Vivid green\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 most prominent color in the image?
A. Red
B. Green
C. Black
D. Blue
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. Green
C. Black
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Red\nB. Green\nC. Black\nD. Blue\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]: 0.7795,[Response]: B.<|endoftext|>, [Correct Ans]: Vivid green, , [Prog]: 1229:  82%|▊| 1230/1495 [07:36<01:35,  2.77it/s]
[Running Accuracy]: 0.7797,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1230:  82%|███████▍ | 1230/1495 [07:36<01:35,  2.77it/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>What is the most prominent color in the image?\nA. Red\nB. Green\nC. Black\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 clearest object in the image?
A. Black top
B. Jeans
C. Umbrella
D. Staircase
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Black top
B. Jeans
C. Umbrella
D. Staircase
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Black top\nB. Jeans\nC. Umbrella\nD. Staircase\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]: 0.7797,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1230:  82%|███████▍ | 1231/1495 [07:36<01:33,  2.83it/s]
[Running Accuracy]: 0.7799,[Response]: A.<|endoftext|>, [Correct Ans]: Black top, , [Prog]: 1231:  82%|██▍| 1231/1495 [07:36<01:33,  2.83it/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>What is the clearest object in the image?\nA. Black top\nB. Jeans\nC. Umbrella\nD. Staircase\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 human this image?
A. Srong
B. Acceptable
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the noise level of the human this image?
A. Srong
B. Acceptable
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the noise level of the human this image?\nA. Srong\nB. Acceptable\nC. Weak\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]: 0.7799,[Response]: A.<|endoftext|>, [Correct Ans]: Black top, , [Prog]: 1231:  82%|██▍| 1232/1495 [07:37<01:27,  3.00it/s]
[Running Accuracy]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 1232:  82%|█████▊ | 1232/1495 [07:37<01:27,  3.00it/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 would you rate the noise level of the human this image?\nA. Srong\nB. Acceptable\nC. Weak\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a 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 clothing worn by the participant in the center of the image high?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the saturation of the clothing worn by the participant in the center of the image high?
A. High
B. Low
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["Is the saturation of the clothing worn by the participant in the center of the image high?\nA. High\nB. Low\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]: 0.7800,[Response]: A.<|endoftext|>, [Correct Ans]: Srong, , [Prog]: 1232:  82%|█████▊ | 1233/1495 [07:37<01:27,  3.00it/s]
[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1233:  82%|███▎| 1233/1495 [07:37<01:27,  3.00it/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>Is the saturation of the clothing worn by the participant in the center of the image high?\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 lighting of this image?
A. Low
B. Dark
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the lighting of this image?
A. Low
B. Dark
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting of this image?\nA. Low\nB. Dark\nC. Acceptable\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]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1233:  83%|███▎| 1234/1495 [07:37<01:25,  3.06it/s]
[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1234:  83%|██████▌ | 1234/1495 [07:37<01:25,  3.06it/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 lighting of this image?\nA. Low\nB. Dark\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 problems are present in the image?
A. Underexposure
B. Motion blur
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problems are present in the image?
A. Underexposure
B. Motion blur
C. Noise
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems are present in the image?\nA. Underexposure\nB. Motion blur\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])
 C.

[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1234:  83%|██████▌ | 1235/1495 [07:38<01:24,  3.06it/s]
[Running Accuracy]: 0.7789,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1235:  83%|█████▊ | 1235/1495 [07:38<01:24,  3.06it/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>What problems are present in the image?\nA. Underexposure\nB. Motion blur\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>How severe is compression artifacts on the cat?
A. None
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How severe is compression artifacts on the cat?
A. None
B. Strong
C. Weak
Answer with the option's letter from the given choices directly.

prompts: [["How severe is compression artifacts on the cat?\nA. None\nB. Strong\nC. Weak\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]: 0.7789,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1235:  83%|█████▊ | 1236/1495 [07:38<01:24,  3.08it/s]
[Running Accuracy]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 1236:  83%|██████▌ | 1236/1495 [07:38<01:24,  3.08it/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 severe is compression artifacts on the cat?\nA. None\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 is emphasized in the composition of the image?
A. Chair
B. Radio
C. Potted plant
D. Blanket
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. Chair
B. Radio
C. Potted plant
D. Blanket
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the composition of the image?\nA. Chair\nB. Radio\nC. Potted plant\nD. Blanket\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]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 1236:  83%|██████▌ | 1237/1495 [07:38<01:23,  3.09it/s]
[Running Accuracy]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Potted plant, , [Prog]: 1237:  83%|▊| 1237/1495 [07:38<01:23,  3.09it/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>Which object is emphasized in the composition of the image?\nA. Chair\nB. Radio\nC. Potted plant\nD. Blanket\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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([-30.9688], 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]: 0.7785,[Response]: C.<|endoftext|>, [Correct Ans]: Potted plant, , [Prog]: 1237:  83%|▊| 1238/1495 [07:39<01:25,  2.99it/s
[Running Accuracy]: 0.7787,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1238:  83%|███████▍ | 1238/1495 [07:39<01:25,  2.99it/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>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>Does this image give a dark visual feeling?
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 feeling?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a dark visual feeling?\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]: 0.7787,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1238:  83%|███████▍ | 1239/1495 [07:39<01:24,  3.02it/s]
[Running Accuracy]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1239:  83%|███████▍ | 1239/1495 [07:39<01:24,  3.02it/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>Does this image give a dark visual feeling?\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 severe image quality problem in the image?
A. Out of focus
B. Overexposure
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most severe image quality problem in the image?
A. Out of focus
B. Overexposure
C. Distortion
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What is the most severe image quality problem in the image?\nA. Out of focus\nB. Overexposure\nC. Distortion\nD. Underexposure\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]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1239:  83%|███████▍ | 1240/1495 [07:39<01:24,  3.01it/s]
[Running Accuracy]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1240:  83%|▊| 1240/1495 [07:39<01:24,  3.01it/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>What is the most severe image quality problem in the image?\nA. Out of focus\nB. Overexposure\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>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([-31.1719], 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]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1240:  83%|▊| 1241/1495 [07:40<01:23,  3.03it/s
[Running Accuracy]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1241:  83%|███████▍ | 1241/1495 [07:40<01:23,  3.03it/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>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': 'B.<|endoftext|>'} 

prompt A chat between a 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 sky vivid in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color of the sky vivid in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the sky vivid in this image?\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]: 0.7784,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1241:  83%|███████▍ | 1242/1495 [07:40<01:44,  2.41it/s]
[Running Accuracy]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1242:  83%|████████▎ | 1242/1495 [07:40<01:44,  2.41it/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>Is the color of the sky vivid 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>How is the color saturation of the diapers 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 diapers 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 diapers in the image?\nA. Good\nB. Average\nC. Poor\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]: 0.7786,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1242:  83%|████████▎ | 1243/1495 [07:40<01:38,  2.56it/s]
[Running Accuracy]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1243:  83%|██████▋ | 1243/1495 [07:40<01:38,  2.56it/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 color saturation of the diapers 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>What is the clearest object in the image?
A. The buildings
B. The woman at the bottom of the image
C. The billboard
D. The woman at the top of the image
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. The buildings
B. The woman at the bottom of the image
C. The billboard
D. The woman at the top of the image
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. The buildings\nB. The woman at the bottom of the image\nC. The billboard\nD. The woman at the top of the image\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]: 0.7788,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1243:  83%|██████▋ | 1244/1495 [07:41<01:33,  2.69it/s]
[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: The woman at the bottom of the image, , [Prog]: 1244:  83%|▊| 1244/1495
 {'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. The buildings\nB. The woman at the bottom of the image\nC. The billboard\nD. The woman at the top of the image\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>Which girl in the picture is in focus?
A. The girl at the right
B. The girl at the back
C. The girl at the left
D. The girl at front
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which girl in the picture is in focus?
A. The girl at the right
B. The girl at the back
C. The girl at the left
D. The girl at front
Answer with the option's letter from the given choices directly.

prompts: [["Which girl in the picture is in focus?\nA. The girl at the right\nB. The girl at the back\nC. The girl at the left\nD. The girl at front\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])
 D.

[Running Accuracy]: 0.7789,[Response]: B.<|endoftext|>, [Correct Ans]: The woman at the bottom of the image, , [Prog]: 1244:  83%|▊| 1245/1495
[Running Accuracy]: 0.7791,[Response]: D.<|endoftext|>, [Correct Ans]: The girl at front, , [Prog]: 1245:  83%|▊| 1245/1495 [07:41<01:30,  2.7
 {'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 girl in the picture is in focus?\nA. The girl at the right\nB. The girl at the back\nC. The girl at the left\nD. The girl at front\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 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 saturation 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 saturation in the image?\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])
 A.

[Running Accuracy]: 0.7791,[Response]: D.<|endoftext|>, [Correct Ans]: The girl at front, , [Prog]: 1245:  83%|▊| 1246/1495 [07:41<01:27,  2.8
[Running Accuracy]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1246:  83%|███████▌ | 1246/1495 [07:41<01:27,  2.85it/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 color saturation 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>Which quality issue exists in the image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Distortion
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which quality issue exists in the image?
A. Overexposure
B. Motion blur
C. Underexposure
D. Distortion
Answer with the option's letter from the given choices directly.

prompts: [["Which quality issue exists in the image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. Distortion\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]: 0.7785,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1246:  83%|███████▌ | 1247/1495 [07:42<01:25,  2.90it/s]
[Running Accuracy]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1247:  83%|▊| 1247/1495 [07:42<01:25,  2.90it/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>Which quality issue exists in the image?\nA. Overexposure\nB. Motion blur\nC. Underexposure\nD. 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>Is the baby 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 baby 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 baby 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([-31.2188], 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]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1247:  83%|▊| 1248/1495 [07:42<01:22,  3.00it/s
[Running Accuracy]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1248:  83%|███████▌ | 1248/1495 [07:42<01:22,  3.00it/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>Is the baby 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 direction does the light come from in the image?
A. Right
B. Left
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which direction does the light come from in the image?
A. Right
B. Left
C. Top
D. Bottom
Answer with the option's letter from the given choices directly.

prompts: [["Which direction does the light come from in the image?\nA. Right\nB. Left\nC. Top\nD. Bottom\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]: 0.7788,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1248:  84%|███████▌ | 1249/1495 [07:42<01:21,  3.02it/s]
[Running Accuracy]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 1249:  84%|█████▊ | 1249/1495 [07:42<01:21,  3.02it/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>Which direction does the light come from in the image?\nA. Right\nB. Left\nC. Top\nD. Bottom\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

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

prompts: [["Is the pigeon the emphasized center in the image composition?\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]: 0.7790,[Response]: A.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 1249:  84%|█████▊ | 1250/1495 [07:43<01:19,  3.08it/s]
[Running Accuracy]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1250:  84%|███████▌ | 1250/1495 [07:43<01:19,  3.08it/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>Is the pigeon the emphasized 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 texture 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 texture 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 texture 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]: 0.7792,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1250:  84%|███████▌ | 1251/1495 [07:43<01:18,  3.10it/s]
[Running Accuracy]: 0.7794,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1251:  84%|██████▋ | 1251/1495 [07:43<01:18,  3.10it/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 texture 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>How blurred is the hawthorn in the picture?
A. Very blurred
B. Not blurred at all
C. A little blurred
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurred is the hawthorn in the picture?
A. Very blurred
B. Not blurred at all
C. A little blurred
Answer with the option's letter from the given choices directly.

prompts: [["How blurred is the hawthorn in the picture?\nA. Very blurred\nB. Not blurred at all\nC. A little blurred\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]: 0.7794,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1251:  84%|██████▋ | 1252/1495 [07:43<01:17,  3.12it/s]
[Running Accuracy]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Not blurred at all, , [Prog]: 1252:  84%|▊| 1252/1495 [07:43<01:17,  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 blurred is the hawthorn in the picture?\nA. Very blurred\nB. Not blurred at all\nC. A little blurred\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a 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 clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the car clear in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the car clear in the image?\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]: 0.7788,[Response]: C.<|endoftext|>, [Correct Ans]: Not blurred at all, , [Prog]: 1252:  84%|▊| 1253/1495 [07:44<01:17,  3.
[Running Accuracy]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1253:  84%|███████▌ | 1253/1495 [07:44<01:17,  3.11it/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>Is the car 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 would you assess the lighting conditions of the wine barrel 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 wine barrel 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 wine barrel in this image?\nA. Bright\nB. Medium\nC. Dark\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-29.9688], 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]: 0.7789,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1253:  84%|███████▌ | 1254/1495 [07:44<01:17,  3.13it/s]
[Running Accuracy]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1254:  84%|██████▋ | 1254/1495 [07:44<01:17,  3.13it/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 would you assess the lighting conditions of the wine barrel 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>Is the man's face clearly visible in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the man's face clearly visible in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the man's face clearly visible in the 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])
 B.

[Running Accuracy]: 0.7783,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1254:  84%|██████▋ | 1255/1495 [07:44<01:16,  3.16it/s]
[Running Accuracy]: 0.7785,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1255:  84%|████████▍ | 1255/1495 [07:44<01:16,  3.16it/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>Is the man's face clearly visible 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 is the color saturation of the flowers 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 flowers 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 flowers in the image?\nA. Good\nB. Poor\nC. Average\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]: 0.7785,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1255:  84%|████████▍ | 1256/1495 [07:45<01:15,  3.16it/s]
[Running Accuracy]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1256:  84%|██████▋ | 1256/1495 [07:45<01:15,  3.16it/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 color saturation of the flowers 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>Which object in this image is emphasized at the center of the composition?
A. Trees
B. Grassland
C. Stones
D. Bridge
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is emphasized at the center of the composition?
A. Trees
B. Grassland
C. Stones
D. Bridge
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is emphasized at the center of the composition?\nA. Trees\nB. Grassland\nC. Stones\nD. Bridge\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])
 D.

[Running Accuracy]: 0.7787,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1256:  84%|██████▋ | 1257/1495 [07:45<01:15,  3.16it/s]
[Running Accuracy]: 0.7788,[Response]: D.<|endoftext|>, [Correct Ans]: Bridge, , [Prog]: 1257:  84%|█████ | 1257/1495 [07:45<01:15,  3.16it/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>Which object in this image is emphasized at the center of the composition?\nA. Trees\nB. Grassland\nC. Stones\nD. Bridge\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>Do the trees in thie picture suffer from underexposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Do the trees in thie picture suffer from underexposure?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Do the trees in thie picture suffer from underexposure?\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]: 0.7788,[Response]: D.<|endoftext|>, [Correct Ans]: Bridge, , [Prog]: 1257:  84%|█████ | 1258/1495 [07:45<01:22,  2.87it/s]
[Running Accuracy]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1258:  84%|███████▌ | 1258/1495 [07:45<01:22,  2.87it/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>Do the trees in thie picture suffer from underexposure?\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 carousel in this image?
A. Moderate
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the carousel in this image?
A. Moderate
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the carousel in this image?\nA. Moderate\nB. Monotonous\nC. Vibrant\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]: 0.7790,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1258:  84%|███████▌ | 1259/1495 [07:46<01:20,  2.94it/s]
[Running Accuracy]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1259:  84%|████▏| 1259/1495 [07:46<01:20,  2.94it/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 color of the carousel in this image?\nA. Moderate\nB. Monotonous\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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([-30.8125], 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]: 0.7792,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1259:  84%|████▏| 1260/1495 [07:46<01:23,  2.82it/s]
[Running Accuracy]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1260:  84%|█████ | 1260/1495 [07:46<01:23,  2.82it/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 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 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([-31.4219], 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]: 0.7794,[Response]: A.<|endoftext|>, [Correct Ans]: Blurry, , [Prog]: 1260:  84%|█████ | 1261/1495 [07:47<01:39,  2.35it/s]
[Running Accuracy]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1261:  84%|█████ | 1261/1495 [07:47<01:39,  2.35it/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 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>From which direction does the light primarily come in the image?
A. Left
B. Top
C. Right
D. Bottom
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light primarily come in the image?
A. Left
B. Top
C. Right
D. Bottom
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light primarily come in the image?\nA. Left\nB. Top\nC. Right\nD. Bottom\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]: 0.7787,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1261:  84%|█████ | 1262/1495 [07:47<01:32,  2.52it/s]
[Running Accuracy]: 0.7781,[Response]: B.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 1262:  84%|█████▉ | 1262/1495 [07:47<01:32,  2.52it/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>From which direction does the light primarily come in the image?\nA. Left\nB. Top\nC. Right\nD. 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>How is the lighting condition of this image?
A. Too dark
B. Too bright
C. Just fine
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. Too bright
C. Just fine
Answer with the option's letter from the given choices directly.

prompts: [["How is the lighting condition of this image?\nA. Too dark\nB. Too bright\nC. Just fine\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]: 0.7781,[Response]: B.<|endoftext|>, [Correct Ans]: Right, , [Prog]: 1262:  84%|█████▉ | 1263/1495 [07:47<01:27,  2.64it/s]
[Running Accuracy]: 0.7775,[Response]: C.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1263:  84%|███▍| 1263/1495 [07:47<01:27,  2.64it/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 lighting condition of this image?\nA. Too dark\nB. Too bright\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>What is the clearest object in the image?
A. Trees
B. Train
C. Utility pole
D. Conductor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest object in the image?
A. Trees
B. Train
C. Utility pole
D. Conductor
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest object in the image?\nA. Trees\nB. Train\nC. Utility pole\nD. Conductor\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]: 0.7775,[Response]: C.<|endoftext|>, [Correct Ans]: Too dark, , [Prog]: 1263:  85%|███▍| 1264/1495 [07:48<01:23,  2.75it/s]
[Running Accuracy]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: Train, , [Prog]: 1264:  85%|█████▉ | 1264/1495 [07:48<01:23,  2.75it/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>What is the clearest object in the image?\nA. Trees\nB. Train\nC. Utility pole\nD. Conductor\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 human in this image?
A. Noise
B. Blur
C. Colorless
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main distortion of the human in this image?
A. Noise
B. Blur
C. Colorless
Answer with the option's letter from the given choices directly.

prompts: [["What is the main distortion of the human in this image?\nA. Noise\nB. Blur\nC. Colorless\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]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: Train, , [Prog]: 1264:  85%|█████▉ | 1265/1495 [07:48<01:41,  2.27it/s]
[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1265:  85%|██████▊ | 1265/1495 [07:48<01:41,  2.27it/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>What is the main distortion of the human in this image?\nA. Noise\nB. Blur\nC. Colorless\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Fair
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Fair\nB. Good\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]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Blur, , [Prog]: 1265:  85%|██████▊ | 1266/1495 [07:49<01:31,  2.51it/s]
[Running Accuracy]: 0.7780,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1266:  85%|██████▊ | 1266/1495 [07:49<01:31,  2.51it/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 clarity of the 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>Does the wall painting contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the wall painting contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the wall painting contain rich texture?\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]: 0.7780,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1266:  85%|██████▊ | 1267/1495 [07:49<01:43,  2.20it/s]
[Running Accuracy]: 0.7782,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1267:  85%|███████▋ | 1267/1495 [07:49<01:43,  2.20it/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>Does the wall painting contain rich 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 texture of the dog clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the texture of the dog clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the texture of the dog 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]: 0.7782,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1267:  85%|███████▋ | 1268/1495 [07:50<01:34,  2.40it/s]
[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1268:  85%|████████▍ | 1268/1495 [07:50<01:34,  2.40it/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>Is the texture of the dog 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 the sky 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 the sky in this image get over-exposed?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the sky in this image get over-exposed?\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])
 A.

[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1268:  85%|████████▍ | 1269/1495 [07:50<01:27,  2.58it/s]
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1269:  85%|███████▋ | 1269/1495 [07:50<01:27,  2.58it/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>Does the sky in this image get over-exposed?\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 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([-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]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1269:  85%|███████▋ | 1270/1495 [07:50<01:23,  2.69it/s]
[Running Accuracy]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1270:  85%|█████▉ | 1270/1495 [07:50<01:23,  2.69it/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 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>How is the color vividity of the image?
A. Relatively vivid
B. Very vivid
C. Moderately faded
D. Totally faded
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color vividity of the image?
A. Relatively vivid
B. Very vivid
C. Moderately faded
D. Totally faded
Answer with the option's letter from the given choices directly.

prompts: [["How is the color vividity of the image?\nA. Relatively vivid\nB. Very vivid\nC. Moderately faded\nD. Totally faded\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]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1270:  85%|█████▉ | 1271/1495 [07:50<01:19,  2.81it/s]
[Running Accuracy]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Totally faded, , [Prog]: 1271:  85%|▊| 1271/1495 [07:50<01:19,  2.81it/
 {'prompt': "A chat between a curious 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. Relatively vivid\nB. Very vivid\nC. Moderately faded\nD. Totally faded\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Bright
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. Bright
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. Bright\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]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Totally faded, , [Prog]: 1271:  85%|▊| 1272/1495 [07:51<01:17,  2.86it/
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1272:  85%|█████ | 1272/1495 [07:51<01:17,  2.86it/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 would you rate the lighting of this image?\nA. Medium\nB. Low\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 the color of the wall 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 wall 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 wall in this image 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]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1272:  85%|█████ | 1273/1495 [07:51<01:15,  2.92it/s]
[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1273:  85%|███████▋ | 1273/1495 [07:51<01:15,  2.92it/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>Is the color of the wall 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>Which part of the image is more blurry, the center or the peripheral areas?
A. The center
B. The peripheral areas
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is more blurry, the center or the peripheral areas?
A. The center
B. The peripheral areas
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is more blurry, the center or the peripheral areas?\nA. The center\nB. The peripheral areas\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]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1273:  85%|███████▋ | 1274/1495 [07:51<01:13,  3.01it/s]
[Running Accuracy]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: The peripheral areas, , [Prog]: 1274:  85%|▊| 1274/1495 [07:51<01:13,  
 {'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>Which part of the image is more blurry, the center or the peripheral areas?\nA. The center\nB. The peripheral areas\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 the blurriest?
A. The trees
B. The yellow building in the distance
C. The grass
D. The blue building nearby
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the picture is the blurriest?
A. The trees
B. The yellow building in the distance
C. The grass
D. The blue building nearby
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the picture is the blurriest?\nA. The trees\nB. The yellow building in the distance\nC. The grass\nD. The blue building nearby\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]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: The peripheral areas, , [Prog]: 1274:  85%|▊| 1275/1495 [07:52<01:11,  
[Running Accuracy]: 0.7757,[Response]: A.<|endoftext|>, [Correct Ans]: The yellow building in the distance, , [Prog]: 1275:  85%|▊| 1275/1495 
 {'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 picture is the blurriest?\nA. The trees\nB. The yellow building in the distance\nC. The grass\nD. The blue building nearby\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 distortion issues in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are there any distortion issues in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are there any distortion issues in the image?\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]: 0.7757,[Response]: A.<|endoftext|>, [Correct Ans]: The yellow building in the distance, , [Prog]: 1275:  85%|▊| 1276/1495 
[Running Accuracy]: 0.7759,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1276:  85%|████████▌ | 1276/1495 [07:52<01:11,  3.06it/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>Are there any distortion issues 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 umbrellas clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the umbrellas clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the umbrellas clear in this image?\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]: 0.7759,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1276:  85%|████████▌ | 1277/1495 [07:53<01:30,  2.42it/s]
[Running Accuracy]: 0.7760,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1277:  85%|████████▌ | 1277/1495 [07:53<01:30,  2.42it/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>Are the umbrellas 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>Are the humans very clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the humans very clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the humans very clear in this image?\nA. Yes\nB. No\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]: 0.7760,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1277:  85%|████████▌ | 1278/1495 [07:53<01:23,  2.61it/s]
[Running Accuracy]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1278:  85%|████████▌ | 1278/1495 [07:53<01:23,  2.61it/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>Are the humans 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>Is the fur of the dog in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the fur of the dog in the image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the fur of the dog in the image clear?\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])
 A.

[Running Accuracy]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1278:  86%|████████▌ | 1279/1495 [07:53<01:19,  2.72it/s]
[Running Accuracy]: 0.7764,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1279:  86%|███████▋ | 1279/1495 [07:53<01:19,  2.72it/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>Is the fur of the dog 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 problems exist in the 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
What problems exist in the image?
A. Overexposure
B. Out of focus
C. Noise
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problems exist in the 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([-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]: 0.7764,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1279:  86%|███████▋ | 1280/1495 [07:54<01:15,  2.85it/s]
[Running Accuracy]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1280:  86%|█████▉ | 1280/1495 [07:54<01:15,  2.85it/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>What problems exist in the 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': 'C.<|endoftext|>'} 

prompt A chat between a curious 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. Acceptable
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the image?
A. Poor
B. Acceptable
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Poor\nB. Acceptable\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])
 A.

[Running Accuracy]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1280:  86%|█████▉ | 1281/1495 [07:54<01:11,  2.98it/s]
[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1281:  86%|██████▊ | 1281/1495 [07:54<01:11,  2.98it/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 clarity of the 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>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([-30.8594], 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]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1281:  86%|██████▊ | 1282/1495 [07:54<01:10,  3.00it/s]
[Running Accuracy]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1282:  86%|███████▋ | 1282/1495 [07:54<01:10,  3.00it/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>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>Is there a problem of defocus in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is there a problem of defocus in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there a problem of defocus in 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])
 B.

[Running Accuracy]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1282:  86%|███████▋ | 1283/1495 [07:55<01:10,  2.99it/s]
[Running Accuracy]: 0.7771,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1283:  86%|████████▌ | 1283/1495 [07:55<01:10,  2.99it/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>Is there a problem of defocus 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 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([-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]: 0.7771,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1283:  86%|████████▌ | 1284/1495 [07:55<01:09,  3.04it/s]
[Running Accuracy]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1284:  86%|█████▏| 1284/1495 [07:55<01:09,  3.04it/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 clarity of this image?\nA. Medium\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>How is the contrast level 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 contrast level in this image?
A. Medium
B. High
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level in this image?\nA. Medium\nB. High\nC. Low\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]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1284:  86%|█████▏| 1285/1495 [07:56<01:25,  2.46it/s]
[Running Accuracy]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1285:  86%|██████▉ | 1285/1495 [07:56<01:25,  2.46it/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 contrast level 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>Is the main color of the fish in the image red?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main color of the fish in the image red?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main color of the fish in the image red?\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]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1285:  86%|██████▉ | 1286/1495 [07:56<01:19,  2.62it/s]
[Running Accuracy]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1286:  86%|████████▌ | 1286/1495 [07:56<01:19,  2.62it/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>Is the main color of the fish in the image red?\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. Man
B. Streetlamp
C. Building
D. Manhole cover
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. Man
B. Streetlamp
C. Building
D. Manhole cover
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center of this image?\nA. Man\nB. Streetlamp\nC. Building\nD. Manhole cover\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]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1286:  86%|████████▌ | 1287/1495 [07:56<01:15,  2.77it/s]
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1287:  86%|███████▋ | 1287/1495 [07:56<01:15,  2.77it/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>Which object is emphasized in the center of this image?\nA. Man\nB. Streetlamp\nC. Building\nD. Manhole cover\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the image clarity?
A. Blurry
B. Clear
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the image clarity?\nA. Blurry\nB. Clear\nC. Average\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]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Man, , [Prog]: 1287:  86%|███████▊ | 1288/1495 [07:57<01:13,  2.80it/s]
[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1288:  86%|██████ | 1288/1495 [07:57<01:13,  2.80it/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?\nA. Blurry\nB. Clear\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 clearest in the image?
A. Woman
B. Wings
C. Clouds
D. White dove
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest in the image?
A. Woman
B. Wings
C. Clouds
D. White dove
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest in the image?\nA. Woman\nB. Wings\nC. Clouds\nD. White dove\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]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1288:  86%|██████ | 1289/1495 [07:57<01:11,  2.88it/s]
[Running Accuracy]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 1289:  86%|██████ | 1289/1495 [07:57<01:11,  2.88it/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>What is the clearest in the image?\nA. Woman\nB. Wings\nC. Clouds\nD. White dove\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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 situation of the ground in the image?
A. Over-exposed
B. Under-exposed
C. Well-exposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the exposure situation of the ground in the image?
A. Over-exposed
B. Under-exposed
C. Well-exposed
Answer with the option's letter from the given choices directly.

prompts: [["What is the exposure situation of the ground in the image?\nA. Over-exposed\nB. Under-exposed\nC. Well-exposed\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]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 1289:  86%|██████ | 1290/1495 [07:57<01:10,  2.91it/s]
[Running Accuracy]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposed, , [Prog]: 1290:  86%|▊| 1290/1495 [07:57<01:10,  2.91it/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>What is the exposure situation of the ground in the image?\nA. Over-exposed\nB. Under-exposed\nC. Well-exposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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([-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]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: Over-exposed, , [Prog]: 1290:  86%|▊| 1291/1495 [07:58<01:09,  2.92it/s
[Running Accuracy]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1291:  86%|██████▉ | 1291/1495 [07:58<01:09,  2.92it/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 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': 'A.<|endoftext|>'} 

prompt A chat between 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([-31.3750], 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]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1291:  86%|██████▉ | 1292/1495 [07:58<01:26,  2.35it/s]
[Running Accuracy]: 0.7771,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1292:  86%|████████▋ | 1292/1495 [07:58<01:26,  2.35it/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>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>Which of the following image quality issues are present in the image?
A. Underexposure
B. Noise
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which of the following image quality issues are present in the image?
A. Underexposure
B. Noise
C. Motion blur
D. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["Which of the following image quality issues are present in the image?\nA. Underexposure\nB. Noise\nC. Motion blur\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])
 B.

[Running Accuracy]: 0.7771,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1292:  86%|████████▋ | 1293/1495 [07:58<01:21,  2.49it/s]
[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1293:  86%|██████ | 1293/1495 [07:58<01:21,  2.49it/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>Which of the following image quality issues are present in the image?\nA. Underexposure\nB. Noise\nC. Motion blur\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 in this image is the focus?
A. The person holding an umbrella
B. The big tree
C. The house
D. The man wearing a black jacket
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. The person holding an umbrella
B. The big tree
C. The house
D. The man wearing a black jacket
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. The person holding an umbrella\nB. The big tree\nC. The house\nD. The man wearing a black jacket\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]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1293:  87%|██████ | 1294/1495 [07:59<01:16,  2.64it/s]
[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: The man wearing a black jacket, , [Prog]: 1294:  87%|▊| 1294/1495 [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 in this image is the focus?\nA. The person holding an umbrella\nB. The big tree\nC. The house\nD. The man wearing a black jacket\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 this image evoke?
A. Fresh
B. Frenetic
C. Dull
D. Dark
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feelings does this image evoke?
A. Fresh
B. Frenetic
C. Dull
D. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feelings does this image evoke?\nA. Fresh\nB. Frenetic\nC. Dull\nD. 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])
 A.

[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: The man wearing a black jacket, , [Prog]: 1294:  87%|▊| 1295/1495 [07:5
[Running Accuracy]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 1295:  87%|██████ | 1295/1495 [07:59<01:13,  2.73it/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>What kind of visual feelings does this image evoke?\nA. Fresh\nB. Frenetic\nC. Dull\nD. 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([-31.2344], 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]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 1295:  87%|██████ | 1296/1495 [07:59<01:09,  2.87it/s]
[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1296:  87%|████████▋ | 1296/1495 [07:59<01:09,  2.87it/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>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 kind of visual impression does the image give?
A. Fresh
B. Vibrant
C. Dull
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. Fresh
B. Vibrant
C. Dull
D. Dark
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual impression does the image give?\nA. Fresh\nB. Vibrant\nC. Dull\nD. Dark\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]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1296:  87%|████████▋ | 1297/1495 [08:00<01:07,  2.95it/s]
[Running Accuracy]: 0.7764,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1297:  87%|██████▉ | 1297/1495 [08:00<01:07,  2.95it/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>What kind of visual impression does the image give?\nA. Fresh\nB. Vibrant\nC. Dull\nD. 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>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([-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]: 0.7764,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1297:  87%|██████▉ | 1298/1495 [08:00<01:05,  3.02it/s]
[Running Accuracy]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1298:  87%|███████▊ | 1298/1495 [08:00<01:05,  3.02it/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>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>How is the exposure of the trees in this image?
A. Appropriate
B. Over-exposure
C. Under-exposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure of the trees in this image?
A. Appropriate
B. Over-exposure
C. Under-exposure
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure of the trees in this image?\nA. Appropriate\nB. Over-exposure\nC. Under-exposure\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]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1298:  87%|███████▊ | 1299/1495 [08:01<01:38,  2.00it/s]
[Running Accuracy]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1299:  87%|▊| 1299/1495 [08:01<01:38,  2.00it
 {'prompt': "A chat between a curious 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 trees in this image?\nA. Appropriate\nB. Over-exposure\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>How is the exposure level of the image?
A. Moderate
B. Underexposed
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. Moderate
B. Underexposed
C. Overexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure level of the image?\nA. Moderate\nB. Underexposed\nC. Overexposed\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])
 A.

[Running Accuracy]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Under-exposure, , [Prog]: 1299:  87%|▊| 1300/1495 [08:01<01:27,  2.23it
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1300:  87%|███▍| 1300/1495 [08:01<01:27,  2.23it/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 exposure level of the image?\nA. Moderate\nB. Underexposed\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 composition of the image with good symmetry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of the image with good symmetry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of the image with good symmetry?\nA. No\nB. Yes\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]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1300:  87%|███▍| 1301/1495 [08:02<01:19,  2.43it/s]
[Running Accuracy]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1301:  87%|███████▊ | 1301/1495 [08:02<01:19,  2.43it/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>Is the composition of the image with good symmetry?\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 little boy wearing a black down jacket clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the little boy wearing a black down jacket clear in this image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the little boy wearing a black down jacket 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]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1301:  87%|███████▊ | 1302/1495 [08:02<01:14,  2.58it/s]
[Running Accuracy]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1302:  87%|████████▋ | 1302/1495 [08:02<01:14,  2.58it/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>Is the little boy wearing a black down jacket 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>What kind of feelings does the image evoke?
A. Depressing
B. Sad
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feelings does the image evoke?
A. Depressing
B. Sad
C. Dark
D. Fresh
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feelings does the image evoke?\nA. Depressing\nB. Sad\nC. Dark\nD. Fresh\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]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1302:  87%|████████▋ | 1303/1495 [08:02<01:10,  2.72it/s]
[Running Accuracy]: 0.7767,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 1303:  87%|██████ | 1303/1495 [08:02<01:10,  2.72it/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>What kind of feelings does the image evoke?\nA. Depressing\nB. Sad\nC. Dark\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>What is the most prominent color in the image?
A. Red
B. White
C. Yellow
D. Blue
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. White
C. Yellow
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Red\nB. White\nC. Yellow\nD. Blue\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]: 0.7767,[Response]: D.<|endoftext|>, [Correct Ans]: Fresh, , [Prog]: 1303:  87%|██████ | 1304/1495 [08:03<01:08,  2.79it/s]
[Running Accuracy]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1304:  87%|███████▊ | 1304/1495 [08:03<01:08,  2.79it/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>What is the most prominent color in the image?\nA. Red\nB. White\nC. Yellow\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 can be found in the image?
A. Motion Blur
B. Noise
C. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion can be found in the image?
A. Motion Blur
B. Noise
C. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion can be found in the image?\nA. Motion Blur\nB. Noise\nC. Underexposure\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]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1304:  87%|███████▊ | 1305/1495 [08:03<01:17,  2.45it/s]
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1305:  87%|▊| 1305/1495 [08:03<01:17,  2.45it/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>What distortion can be found in the image?\nA. Motion Blur\nB. Noise\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 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([-31.6875], 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]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1305:  87%|▊| 1306/1495 [08:04<01:14,  2.54it/s]
[Running Accuracy]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1306:  87%|████████▋ | 1306/1495 [08:04<01:14,  2.54it/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>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>How is the lighting of the background 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 background 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 background in this image?\nA. Dark\nB. Medium\nC. Bright\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]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1306:  87%|████████▋ | 1307/1495 [08:04<01:10,  2.67it/s]
[Running Accuracy]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1307:  87%|██████▉ | 1307/1495 [08:04<01:10,  2.67it/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 lighting of the background 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>How clear are the characters in this picture?
A. Clear
B. Fair
C. Blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear are the characters in this picture?
A. Clear
B. Fair
C. Blurry
Answer with the option's letter from the given choices directly.

prompts: [["How clear are the characters in this picture?\nA. Clear\nB. Fair\nC. Blurry\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]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1307:  87%|██████▉ | 1308/1495 [08:04<01:20,  2.32it/s]
[Running Accuracy]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1308:  87%|██████ | 1308/1495 [08:04<01:20,  2.32it/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 clear are the characters in this picture?\nA. Clear\nB. Fair\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>Is this image with vivid colors?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image with vivid colors?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image with vivid colors?\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]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1308:  88%|██████▏| 1309/1495 [08:05<01:15,  2.47it/s]
[Running Accuracy]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1309:  88%|███████▉ | 1309/1495 [08:05<01:15,  2.47it/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>Is this image with vivid colors?\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's the worst distortion in this picture?
A. Out of focus
B. Motion blur
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. Out of focus
B. Motion blur
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. Out of focus\nB. Motion blur\nC. Noise\nD. Overexposure\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]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1309:  88%|███████▉ | 1310/1495 [08:05<01:09,  2.67it/s]
[Running Accuracy]: 0.7771,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1310:  88%|██████▏| 1310/1495 [08:05<01:09,  2.67it/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>What's the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\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>What is the most prominent color in the image?
A. Yellow
B. Purple
C. Red
D. Blue
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most prominent color in the image?
A. Yellow
B. Purple
C. Red
D. Blue
Answer with the option's letter from the given choices directly.

prompts: [["What is the most prominent color in the image?\nA. Yellow\nB. Purple\nC. Red\nD. Blue\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]: 0.7771,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1310:  88%|██████▏| 1311/1495 [08:05<01:06,  2.77it/s]
[Running Accuracy]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 1311:  88%|█████▎| 1311/1495 [08:05<01:06,  2.77it/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>What is the most prominent color in the image?\nA. Yellow\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>Which part of the image is the clearest?
A. The building
B. The vehicle in the lower left corner
C. Pedestrians
D. The vehicle on the right side
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of the image is the clearest?
A. The building
B. The vehicle in the lower left corner
C. Pedestrians
D. The vehicle on the right side
Answer with the option's letter from the given choices directly.

prompts: [["Which part of the image is the clearest?\nA. The building\nB. The vehicle in the lower left corner\nC. Pedestrians\nD. The vehicle on the right side\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]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 1311:  88%|█████▎| 1312/1495 [08:06<01:04,  2.83it/s]
[Running Accuracy]: 0.7774,[Response]: B.<|endoftext|>, [Correct Ans]: The vehicle in the lower left corner, , [Prog]: 1312:  88%|▉| 1312/1495
 {'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 clearest?\nA. The building\nB. The vehicle in the lower left corner\nC. Pedestrians\nD. The vehicle on the right side\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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. Green
D. Blue
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. Green
D. Blue
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. 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])
 B.

[Running Accuracy]: 0.7774,[Response]: B.<|endoftext|>, [Correct Ans]: The vehicle in the lower left corner, , [Prog]: 1312:  88%|▉| 1313/1495
[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 1313:  88%|█████▎| 1313/1495 [08:06<01:02,  2.90it/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>What is the most prominent color in the image?\nA. Red\nB. Yellow\nC. Green\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>Is there any issue with 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 issue with compression distortion in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there any issue with compression distortion in the image?\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])
 A.

[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yellow, , [Prog]: 1313:  88%|█████▎| 1314/1495 [08:06<01:02,  2.92it/s]
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1314:  88%|████████▊ | 1314/1495 [08:06<01:02,  2.92it/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>Is there any issue with compression distortion 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 exposure level of the faces in the image?
A. Moderate
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure level of the faces in the image?
A. Moderate
B. Overexposed
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure level of the faces in the image?\nA. Moderate\nB. Overexposed\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])
 A.

[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1314:  88%|████████▊ | 1315/1495 [08:07<01:00,  2.99it/s]
[Running Accuracy]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1315:  88%|███▌| 1315/1495 [08:07<01:00,  2.99it/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 exposure level of the faces 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>Which object is the main focus in this image?
A. Trees
B. Bamboo
C. Panda
D. Person
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the main focus in this image?
A. Trees
B. Bamboo
C. Panda
D. Person
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the main focus in this image?\nA. Trees\nB. Bamboo\nC. Panda\nD. Person\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]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1315:  88%|███▌| 1316/1495 [08:07<00:59,  3.01it/s]
[Running Accuracy]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 1316:  88%|██████▏| 1316/1495 [08:07<00:59,  3.01it/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>Which object is the main focus in this image?\nA. Trees\nB. Bamboo\nC. Panda\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>How is the clarity of the gondolas this image?
A. High
B. Low
C. Average
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the clarity of the gondolas this image?
A. High
B. Low
C. Average
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the gondolas this image?\nA. High\nB. Low\nC. Average\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]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 1316:  88%|██████▏| 1317/1495 [08:07<00:59,  2.99it/s]
[Running Accuracy]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1317:  88%|███████▉ | 1317/1495 [08:07<00:59,  2.99it/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 clarity of the gondolas this image?\nA. High\nB. Low\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 color 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 color 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 color saturation of the image?\nA. Poor\nB. Average\nC. Good\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.0312], 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]: 0.7775,[Response]: B.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1317:  88%|███████▉ | 1318/1495 [08:08<00:57,  3.06it/s]
[Running Accuracy]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1318:  88%|███████ | 1318/1495 [08:08<00:57,  3.06it/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 color saturation of the image?\nA. Poor\nB. Average\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 color of the books on the bookshelf in this image?
A. Monotonous
B. Vibrant
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the books on the bookshelf in this image?
A. Monotonous
B. Vibrant
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the books on the bookshelf in this image?\nA. Monotonous\nB. Vibrant\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])
 A.

[Running Accuracy]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1318:  88%|███████ | 1319/1495 [08:08<00:58,  3.03it/s]
[Running Accuracy]: 0.7771,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1319:  88%|█████▎| 1319/1495 [08:08<00:58,  3.03it/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 color of the books on the bookshelf in this image?\nA. Monotonous\nB. Vibrant\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>Does this image give a fresh 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 fresh visual experience?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image give a fresh visual experience?\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]: 0.7771,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1319:  88%|█████▎| 1320/1495 [08:08<00:56,  3.10it/s]
[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1320:  88%|███████▉ | 1320/1495 [08:08<00:56,  3.10it/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>Does this image give a fresh 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>What is the most colorful object in this picture?
A. Sky
B. Trees
C. Farmland
D. The people standing in the center
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the most colorful object in this picture?
A. Sky
B. Trees
C. Farmland
D. The people standing in the center
Answer with the option's letter from the given choices directly.

prompts: [["What is the most colorful object in this picture?\nA. Sky\nB. Trees\nC. Farmland\nD. The people standing in the center\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])
 D.

[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1320:  88%|███████▉ | 1321/1495 [08:09<01:26,  2.00it/s]
[Running Accuracy]: 0.7774,[Response]: D.<|endoftext|>, [Correct Ans]: The people standing in the center, , [Prog]: 1321:  88%|▉| 1321/1495 [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 colorful object in this picture?\nA. Sky\nB. Trees\nC. Farmland\nD. The people standing in the center\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 animals affected by blur in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the animals affected by blur in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the animals affected by blur 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]: 0.7774,[Response]: D.<|endoftext|>, [Correct Ans]: The people standing in the center, , [Prog]: 1321:  88%|▉| 1322/1495 [0
[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1322:  88%|███████▉ | 1322/1495 [08:10<01:17,  2.23it/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>Are the animals affected by blur 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 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 most apparent distortion of 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 most apparent distortion of this image?\nA. Noise\nB. Over-exposure\nC. Motion blur\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.1094], 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]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1322:  88%|███████▉ | 1323/1495 [08:10<01:10,  2.45it/s]
[Running Accuracy]: 0.7778,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1323:  88%|▉| 1323/1495 [08:10<01:10,  2.45it/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>What is the most apparent distortion of 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>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([-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]: 0.7778,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1323:  89%|▉| 1324/1495 [08:10<01:05,  2.63it/s]
[Running Accuracy]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1324:  89%|███████ | 1324/1495 [08:10<01:05,  2.63it/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 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>Which part of this image is the clearest?
A. Ground
B. Buildings
C. Red Car
D. White 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. Buildings
C. Red Car
D. White Car
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the clearest?\nA. Ground\nB. Buildings\nC. Red Car\nD. White Car\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]: 0.7779,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1324:  89%|███████ | 1325/1495 [08:10<01:00,  2.80it/s]
[Running Accuracy]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Red Car, , [Prog]: 1325:  89%|████▍| 1325/1495 [08:10<01:00,  2.80it/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>Which part of this image is the clearest?\nA. Ground\nB. Buildings\nC. Red Car\nD. White 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>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([-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]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Red Car, , [Prog]: 1325:  89%|████▍| 1326/1495 [08:11<00:59,  2.86it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1326:  89%|███████ | 1326/1495 [08:11<00:59,  2.86it/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 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': 'A.<|endoftext|>'} 

prompt A chat between 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 dimly-lit?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image dimly-lit?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is this image dimly-lit?\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]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1326:  89%|███████ | 1327/1495 [08:11<00:58,  2.85it/s]
[Running Accuracy]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1327:  89%|████████▉ | 1327/1495 [08:11<00:58,  2.85it/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>Is this image dimly-lit?\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 this image is the clearest?
A. ground
B. tree
C. sky
D. person
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. tree
C. sky
D. person
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the clearest?\nA. ground\nB. tree\nC. sky\nD. person\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]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1327:  89%|████████▉ | 1328/1495 [08:12<01:06,  2.53it/s]
[Running Accuracy]: 0.7779,[Response]: D.<|endoftext|>, [Correct Ans]: person, , [Prog]: 1328:  89%|█████▎| 1328/1495 [08:12<01:06,  2.53it/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>Which part of this image is the clearest?\nA. ground\nB. tree\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 there an underexposure issue 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 issue in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is there an underexposure issue in the image?\nA. Yes\nB. No\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]: 0.7779,[Response]: D.<|endoftext|>, [Correct Ans]: person, , [Prog]: 1328:  89%|█████▎| 1329/1495 [08:12<01:02,  2.66it/s]
[Running Accuracy]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1329:  89%|████████▉ | 1329/1495 [08:12<01:02,  2.66it/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>Is there an underexposure issue 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 sharpness of the image?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the sharpness of the image?
A. Acceptable
B. Excellent
C. Bad
Answer with the option's letter from the given choices directly.

prompts: [["How is the sharpness of the image?\nA. Acceptable\nB. Excellent\nC. Bad\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]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1329:  89%|████████▉ | 1330/1495 [08:12<00:59,  2.78it/s]
[Running Accuracy]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 1330:  89%|████████ | 1330/1495 [08:12<00:59,  2.78it/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 sharpness of the 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>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([-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]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 1330:  89%|████████ | 1331/1495 [08:13<00:56,  2.90it/s]
[Running Accuracy]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1331:  89%|███████ | 1331/1495 [08:13<00:56,  2.90it/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 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 composition of this image centered?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image centered?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image centered?\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]: 0.7776,[Response]: B.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1331:  89%|███████▏| 1332/1495 [08:13<00:55,  2.94it/s]
[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1332:  89%|████████▉ | 1332/1495 [08:13<00:55,  2.94it/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>Is the composition of this image centered?\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 style of the image?
A. Blueish
B. Greenish
C. Grayish
D. Reddish
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color style of the image?
A. Blueish
B. Greenish
C. Grayish
D. Reddish
Answer with the option's letter from the given choices directly.

prompts: [["How is the color style of the image?\nA. Blueish\nB. Greenish\nC. Grayish\nD. Reddish\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]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1332:  89%|████████▉ | 1333/1495 [08:14<01:08,  2.37it/s]
[Running Accuracy]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: Grayish, , [Prog]: 1333:  89%|████▍| 1333/1495 [08:14<01:08,  2.37it/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 color style of the image?\nA. Blueish\nB. Greenish\nC. Grayish\nD. Reddish\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 happens in this image?
A. Motion Blur
B. Noise
C. Out of Focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion happens in this image?
A. Motion Blur
B. Noise
C. Out of Focus
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion happens in this image?\nA. Motion Blur\nB. Noise\nC. Out of Focus\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]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: Grayish, , [Prog]: 1333:  89%|████▍| 1334/1495 [08:14<01:10,  2.29it/s]
[Running Accuracy]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 1334:  89%|▉| 1334/1495 [08:14<01:10,  2.29it/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>Which distortion happens in this image?\nA. Motion Blur\nB. Noise\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>Which object is the focus in this image?
A. Bridge
B. Sky
C. Grassland
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. Bridge
B. Sky
C. Grassland
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. Bridge\nB. Sky\nC. Grassland\nD. Trees\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]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Out of Focus, , [Prog]: 1334:  89%|▉| 1335/1495 [08:14<01:04,  2.47it/s
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Bridge, , [Prog]: 1335:  89%|█████▎| 1335/1495 [08:14<01:04,  2.47it/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>Which object is the focus in this image?\nA. Bridge\nB. Sky\nC. Grassland\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>Does this image have very strong noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have very strong noise?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have very strong noise?\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]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Bridge, , [Prog]: 1335:  89%|█████▎| 1336/1495 [08:15<01:00,  2.63it/s]
[Running Accuracy]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1336:  89%|████████ | 1336/1495 [08:15<01:00,  2.63it/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>Does this image have very strong 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 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([-31.1250], 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]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1336:  89%|████████ | 1337/1495 [08:15<00:57,  2.76it/s]
[Running Accuracy]: 0.7771,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1337:  89%|▉| 1337/1495 [08:15<00:57,  2.76it/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>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>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([-30.8438], 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]: 0.7771,[Response]: D.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1337:  89%|▉| 1338/1495 [08:15<00:54,  2.88it/s
[Running Accuracy]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1338:  89%|████████ | 1338/1495 [08:15<00:54,  2.88it/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>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>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([-31.1406], 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]: 0.7773,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1338:  90%|████████ | 1339/1495 [08:16<00:52,  2.96it/s]
[Running Accuracy]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1339:  90%|▉| 1339/1495 [08:16<00:52,  2.96it/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>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': 'C.<|endoftext|>'} 

prompt A chat 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([-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]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1339:  90%|▉| 1340/1495 [08:16<00:50,  3.08it/s
[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1340:  90%|████████ | 1340/1495 [08:16<00:50,  3.08it/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>Does this picture 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>How would you rate the lighting of the ceiling of this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of the ceiling of this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of the ceiling of this image?\nA. Bright\nB. Dark\nC. Medium\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]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1340:  90%|████████ | 1341/1495 [08:16<00:49,  3.10it/s]
[Running Accuracy]: 0.7770,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1341:  90%|███████▏| 1341/1495 [08:16<00:49,  3.10it/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 would you rate the lighting of the ceiling of this image?\nA. Bright\nB. 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>Does this image appear black and white?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image appear black and white?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image appear black and white?\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]: 0.7770,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1341:  90%|███████▏| 1342/1495 [08:17<00:51,  2.95it/s]
[Running Accuracy]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1342:  90%|████████▉ | 1342/1495 [08:17<00:51,  2.95it/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>Does this image appear black and white?\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>From which direction is the light coming in the image?
A. Bottom right
B. Top right
C. Bottom left
D. Top left
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction is the light coming in the image?
A. Bottom right
B. Top right
C. Bottom left
D. Top left
Answer with the option's letter from the given choices directly.

prompts: [["From which direction is the light coming in the image?\nA. Bottom right\nB. Top right\nC. Bottom left\nD. Top left\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]: 0.7772,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1342:  90%|████████▉ | 1343/1495 [08:17<00:50,  3.00it/s]
[Running Accuracy]: 0.7774,[Response]: B.<|endoftext|>, [Correct Ans]: Top right, , [Prog]: 1343:  90%|██▋| 1343/1495 [08:17<00:50,  3.00it/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>From which direction is the light coming in the image?\nA. Bottom right\nB. Top right\nC. Bottom left\nD. Top left\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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 grass in this image?
A. Vibrant
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the grass in this image?
A. Vibrant
B. Monotonous
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the grass in this image?\nA. Vibrant\nB. Monotonous\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]: 0.7774,[Response]: B.<|endoftext|>, [Correct Ans]: Top right, , [Prog]: 1343:  90%|██▋| 1344/1495 [08:17<00:51,  2.96it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1344:  90%|████▍| 1344/1495 [08:17<00:51,  2.96it/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 color of the grass in this image?\nA. Vibrant\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>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([-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])
 B.

[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1344:  90%|████▍| 1345/1495 [08:18<00:49,  3.03it/s]
[Running Accuracy]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1345:  90%|████████ | 1345/1495 [08:18<00:49,  3.03it/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>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>How is the color of the balls in this image?
A. Average
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the balls in this image?
A. Average
B. Monotonous
C. Vibrant
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the balls in this image?\nA. Average\nB. Monotonous\nC. Vibrant\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]: 0.7777,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1345:  90%|████████ | 1346/1495 [08:18<00:48,  3.09it/s]
[Running Accuracy]: 0.7779,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1346:  90%|████▌| 1346/1495 [08:18<00:48,  3.09it/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 color of the balls in this image?\nA. Average\nB. Monotonous\nC. Vibrant\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 robot in the image?
A. Overexposed
B. Underexposed
C. Optimal
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the exposure level of the robot in the image?
A. Overexposed
B. Underexposed
C. Optimal
Answer with the option's letter from the given choices directly.

prompts: [["How is the exposure level of the robot in the image?\nA. Overexposed\nB. Underexposed\nC. Optimal\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]: 0.7779,[Response]: C.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1346:  90%|████▌| 1347/1495 [08:18<00:47,  3.12it/s]
[Running Accuracy]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 1347:  90%|▉| 1347/1495 [08:18<00:47,  3.12it/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 exposure level of the robot in the image?\nA. Overexposed\nB. Underexposed\nC. Optimal\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between a curious 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 bird 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 main distortion for the bird 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 main distortion for the bird 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([-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]: 0.7773,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposed, , [Prog]: 1347:  90%|▉| 1348/1495 [08:19<00:47,  3.09it/s]
[Running Accuracy]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1348:  90%|▉| 1348/1495 [08:19<00:47,  3.09it/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>What is the main distortion for the bird 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>Does this image look photo-realistic or computer-generated?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?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?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]: 0.7774,[Response]: C.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1348:  90%|▉| 1349/1495 [08:19<00:46,  3.11it/s]
[Running Accuracy]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1349:  90%|▉| 1349/1495 [08:19<00:46,  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 look photo-realistic or computer-generated?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>How would you rate the clarity of the flowers?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the clarity of the flowers?
A. Low
B. High
C. Acceptable
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the clarity of the flowers?\nA. Low\nB. High\nC. Acceptable\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]: 0.7776,[Response]: A.<|endoftext|>, [Correct Ans]: Computer-generated, , [Prog]: 1349:  90%|▉| 1350/1495 [08:19<00:58,  2.
[Running Accuracy]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1350:  90%|████████▏| 1350/1495 [08:19<00:58,  2.49it/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 would you rate the clarity of the flowers?\nA. Low\nB. High\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 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([-31.1250], 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]: 0.7778,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1350:  90%|████████▏| 1351/1495 [08:20<01:10,  2.04it/s]
[Running Accuracy]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1351:  90%|████████▏| 1351/1495 [08:20<01:10,  2.04it/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>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>From which direction does the light come in the image?
A. Top right
B. Bottom left
C. Top left
D. Bottom right
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
From which direction does the light come in the image?
A. Top right
B. Bottom left
C. Top left
D. Bottom right
Answer with the option's letter from the given choices directly.

prompts: [["From which direction does the light come in the image?\nA. Top right\nB. Bottom left\nC. Top left\nD. Bottom right\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]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1351:  90%|████████▏| 1352/1495 [08:20<01:02,  2.29it/s]
[Running Accuracy]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Top left, , [Prog]: 1352:  90%|███▌| 1352/1495 [08:20<01:02,  2.29it/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>From which direction does the light come in the image?\nA. Top right\nB. Bottom left\nC. Top left\nD. Bottom 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>Does this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have motion blur?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have motion blur?\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]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Top left, , [Prog]: 1352:  91%|███▌| 1353/1495 [08:21<00:56,  2.50it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1353:  91%|█████████ | 1353/1495 [08:21<00:56,  2.50it/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>Does this picture have motion blur?\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([-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])
 A.

[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1353:  91%|█████████ | 1354/1495 [08:21<00:52,  2.67it/s]
[Running Accuracy]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1354:  91%|█████████ | 1354/1495 [08:21<00:52,  2.67it/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>Is this image well-composed?\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 of the Christmas tree in this image?
A. Bright
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the Christmas tree in this image?
A. Bright
B. Monotonous
C. Moderate
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the Christmas tree in this image?\nA. Bright\nB. Monotonous\nC. Moderate\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]: 0.7777,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1354:  91%|█████████ | 1355/1495 [08:21<00:49,  2.81it/s]
[Running Accuracy]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1355:  91%|█████▍| 1355/1495 [08:21<00:49,  2.81it/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 color of the Christmas tree in this image?\nA. Bright\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>Is the motorcycle 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 motorcycle 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 motorcycle 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([-31.2344], 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]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1355:  91%|█████▍| 1356/1495 [08:22<00:48,  2.89it/s]
[Running Accuracy]: 0.7780,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1356:  91%|████████▏| 1356/1495 [08:22<00:48,  2.89it/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>Is the motorcycle 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 texture sharpness of the parachute?
A. Low
B. Fair
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the texture sharpness of the parachute?
A. Low
B. Fair
C. High
Answer with the option's letter from the given choices directly.

prompts: [["How is the texture sharpness of the parachute?\nA. Low\nB. Fair\nC. High\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]: 0.7780,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1356:  91%|████████▏| 1357/1495 [08:22<00:47,  2.93it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1357:  91%|███████▎| 1357/1495 [08:22<00:47,  2.93it/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 texture sharpness of the parachute?\nA. Low\nB. Fair\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 color saturation of the puppy in the image high?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the puppy in the image high?
A. Medium
B. Low
C. High
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the puppy in the image high?\nA. Medium\nB. Low\nC. High\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]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Fair, , [Prog]: 1357:  91%|███████▎| 1358/1495 [08:22<00:45,  3.00it/s]
[Running Accuracy]: 0.7776,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1358:  91%|███████▎| 1358/1495 [08:22<00:45,  3.00it/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>Is the color saturation of the puppy in the image high?\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 brightest object in this picture?
A. Water
B. Rubber ducks
C. Windows
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest object in this picture?
A. Water
B. Rubber ducks
C. Windows
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest object in this picture?\nA. Water\nB. Rubber ducks\nC. Windows\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]: 0.7776,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1358:  91%|███████▎| 1359/1495 [08:23<00:45,  2.98it/s]
[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Rubber ducks, , [Prog]: 1359:  91%|▉| 1359/1495 [08:23<00:45,  2.98it/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>What is the brightest object in this picture?\nA. Water\nB. Rubber ducks\nC. Windows\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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([-30.8125], 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]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Rubber ducks, , [Prog]: 1359:  91%|▉| 1360/1495 [08:23<00:44,  3.02it/s
[Running Accuracy]: 0.7779,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1360:  91%|███▋| 1360/1495 [08:23<00:44,  3.02it/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 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 clarity of the animate characters 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 animate characters 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 animate characters in this image?\nA. Low\nB. Medium\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])
 C.

[Running Accuracy]: 0.7779,[Response]: C.<|endoftext|>, [Correct Ans]: Colorful, , [Prog]: 1360:  91%|███▋| 1361/1495 [08:23<00:44,  3.01it/s]
[Running Accuracy]: 0.7781,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1361:  91%|███████▎| 1361/1495 [08:23<00:44,  3.01it/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 clarity of the animate characters in 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>Is the kitten clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the kitten clear in the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the kitten 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])
 A.

[Running Accuracy]: 0.7781,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1361:  91%|███████▎| 1362/1495 [08:24<00:43,  3.08it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1362:  91%|████████▏| 1362/1495 [08:24<00:43,  3.08it/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>Is the kitten 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>How is the overall 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 is the overall clarity 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 clarity of this image?\nA. Low\nB. Medium\nC. High\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2188], 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]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1362:  91%|████████▏| 1363/1495 [08:24<00:44,  2.94it/s]
[Running Accuracy]: 0.7777,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1363:  91%|███████▎| 1363/1495 [08:24<00:44,  2.94it/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 overall clarity 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>Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise?\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])
 A.

[Running Accuracy]: 0.7777,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1363:  91%|███████▎| 1364/1495 [08:24<00:45,  2.87it/s]
[Running Accuracy]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1364:  91%|█████████ | 1364/1495 [08:24<00:45,  2.87it/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>Does this picture have 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>Does the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the ground contain rich texture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the ground contain rich texture?\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]: 0.7779,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1364:  91%|█████████▏| 1365/1495 [08:25<00:51,  2.50it/s]
[Running Accuracy]: 0.7780,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1365:  91%|████████▏| 1365/1495 [08:25<00:51,  2.50it/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>Does 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 distortion does not exist in this image?
A. Underexposure
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What distortion does not exist in this image?
A. Underexposure
B. Noise
C. Overexposure
Answer with the option's letter from the given choices directly.

prompts: [["What distortion does not exist in this image?\nA. Underexposure\nB. Noise\nC. 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])
 A.

[Running Accuracy]: 0.7780,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1365:  91%|████████▏| 1366/1495 [08:25<00:47,  2.69it/s]
[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1366:  91%|██████▍| 1366/1495 [08:25<00:47,  2.69it/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>What distortion does not exist in this image?\nA. Underexposure\nB. Noise\nC. 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 is the clarity of the girl 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 girl 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 girl in 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])
 C.

[Running Accuracy]: 0.7775,[Response]: A.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1366:  91%|██████▍| 1367/1495 [08:26<00:45,  2.82it/s]
[Running Accuracy]: 0.7776,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1367:  91%|███████▎| 1367/1495 [08:26<00:45,  2.82it/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 clarity of the girl in 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 color is the brightest part in this image?
A. Blue
B. Red
C. Yellow
D. Green
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What color is the brightest part in this image?
A. Blue
B. Red
C. Yellow
D. Green
Answer with the option's letter from the given choices directly.

prompts: [["What color is the brightest part in this image?\nA. Blue\nB. Red\nC. Yellow\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])
 B.

[Running Accuracy]: 0.7776,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1367:  92%|███████▎| 1368/1495 [08:26<00:43,  2.89it/s]
[Running Accuracy]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1368:  92%|████████▏| 1368/1495 [08:26<00:43,  2.89it/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>What color is the brightest part in this image?\nA. Blue\nB. Red\nC. Yellow\nD. Green\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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 picture come from below?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the light in this picture come from below?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the light in this picture come from below?\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]: 0.7778,[Response]: B.<|endoftext|>, [Correct Ans]: Red, , [Prog]: 1368:  92%|████████▏| 1369/1495 [08:26<00:44,  2.82it/s]
[Running Accuracy]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1369:  92%|█████████▏| 1369/1495 [08:26<00:44,  2.82it/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>Does the light in this picture come from below?\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 apple in the image?
A. Good
B. Average
C. Not applicable
D. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color saturation of the apple in the image?
A. Good
B. Average
C. Not applicable
D. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the color saturation of the apple in the image?\nA. Good\nB. Average\nC. Not applicable\nD. Poor\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]: 0.7772,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1369:  92%|█████████▏| 1370/1495 [08:27<00:42,  2.95it/s]
[Running Accuracy]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1370:  92%|███████▎| 1370/1495 [08:27<00:42,  2.95it/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 color saturation of the apple in the image?\nA. Good\nB. Average\nC. Not applicable\nD. 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 blur level of the image?
A. Not blurry at all
B. Some blur
C. Very blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the blur level of the image?
A. Not blurry at all
B. Some blur
C. Very blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the blur level of the image?\nA. Not blurry at all\nB. Some blur\nC. Very blurry\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]: 0.7774,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1370:  92%|███████▎| 1371/1495 [08:27<00:41,  2.97it/s]
[Running Accuracy]: 0.7768,[Response]: C.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 1371:  92%|██▊| 1371/1495 [08:27<00:41,  2.97it/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>What is the blur level of the image?\nA. Not blurry at all\nB. Some blur\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>Does the image have excessive noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image have excessive noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does the image have excessive noise?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.1719], 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]: 0.7768,[Response]: C.<|endoftext|>, [Correct Ans]: Some blur, , [Prog]: 1371:  92%|██▊| 1372/1495 [08:27<00:40,  3.05it/s]
[Running Accuracy]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1372:  92%|████████▎| 1372/1495 [08:27<00:40,  3.05it/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>Does the image have excessive 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>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([-31.0938], 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]: 0.7770,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1372:  92%|████████▎| 1373/1495 [08:28<00:39,  3.11it/s]
[Running Accuracy]: 0.7764,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1373:  92%|███████▎| 1373/1495 [08:28<00:39,  3.11it/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 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 brightness of the plush toy 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 brightness of the plush toy in this 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 plush toy in this image?\nA. Low\nB. Medium\nC. High\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])
 A.

[Running Accuracy]: 0.7764,[Response]: C.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1373:  92%|███████▎| 1374/1495 [08:28<00:39,  3.09it/s]
[Running Accuracy]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1374:  92%|███████▎| 1374/1495 [08:28<00:39,  3.09it/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 brightness of the plush toy 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>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([-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]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1374:  92%|███████▎| 1375/1495 [08:28<00:39,  3.06it/s]
[Running Accuracy]: 0.7753,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1375:  92%|█████▌| 1375/1495 [08:28<00:39,  3.06it/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 clear is this picture?\nA. Normal\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>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([-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]: 0.7753,[Response]: B.<|endoftext|>, [Correct Ans]: Normal, , [Prog]: 1375:  92%|█████▌| 1376/1495 [08:29<00:38,  3.08it/s]
[Running Accuracy]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1376:  92%|████████▎| 1376/1495 [08:29<00:38,  3.08it/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>Is the image color saturated?\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 in the image is the focus?
A. Halo
B. Planet
C. Starry sky
D. Horizon
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is the focus?
A. Halo
B. Planet
C. Starry sky
D. Horizon
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is the focus?\nA. Halo\nB. Planet\nC. Starry sky\nD. Horizon\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]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1376:  92%|████████▎| 1377/1495 [08:29<00:37,  3.13it/s]
[Running Accuracy]: 0.7756,[Response]: B.<|endoftext|>, [Correct Ans]: Planet, , [Prog]: 1377:  92%|█████▌| 1377/1495 [08:29<00:37,  3.13it/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>Which object in the image is the focus?\nA. Halo\nB. Planet\nC. Starry sky\nD. Horizon\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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. Meidum
B. Low
C. Bright
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the lighting of this image?
A. Meidum
B. Low
C. Bright
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the lighting of this image?\nA. Meidum\nB. Low\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]: 0.7756,[Response]: B.<|endoftext|>, [Correct Ans]: Planet, , [Prog]: 1377:  92%|█████▌| 1378/1495 [08:29<00:36,  3.16it/s]
[Running Accuracy]: 0.7758,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1378:  92%|█████▌| 1378/1495 [08:29<00:36,  3.16it/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 would you rate the lighting of this image?\nA. Meidum\nB. Low\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 woman's top the most saturated object in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman's top the most saturated object in the image?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman's top the most saturated object 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]: 0.7758,[Response]: C.<|endoftext|>, [Correct Ans]: Bright, , [Prog]: 1378:  92%|█████▌| 1379/1495 [08:29<00:36,  3.14it/s]
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1379:  92%|████████▎| 1379/1495 [08:29<00:36,  3.14it/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>Is the woman's top the most saturated object 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 the lighting sufficient for the pine tree 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 lighting sufficient for the pine tree in the center of the image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the lighting sufficient for the pine tree in the center of the image?\nA. No\nB. Yes\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.2969], 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]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1379:  92%|████████▎| 1380/1495 [08:30<00:36,  3.17it/s]
[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1380:  92%|████████▎| 1380/1495 [08:30<00:36,  3.17it/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>Is the lighting sufficient for the pine tree 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>What is the degree of blurriness in the image?
A. Very blurry
B. Completely unblurred
C. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the degree of blurriness in the image?
A. Very blurry
B. Completely unblurred
C. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["What is the degree of blurriness in the image?\nA. Very blurry\nB. Completely unblurred\nC. Slightly 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])
 C.

[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1380:  92%|████████▎| 1381/1495 [08:30<00:35,  3.20it/s]
[Running Accuracy]: 0.7762,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1381:  92%|▉| 1381/1495 [08:30<00:35,  3.20i
 {'prompt': "A chat between a curious 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?\nA. Very blurry\nB. Completely unblurred\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 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([-31.2031], 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]: 0.7762,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1381:  92%|▉| 1382/1495 [08:30<00:35,  3.22i
[Running Accuracy]: 0.7764,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1382:  92%|████████▎| 1382/1495 [08:30<00:35,  3.22it/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>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>Which image quality issue does not exist in this image?
A. Noise
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which image quality issue does not exist in this image?
A. Noise
B. Overexposure
C. Underexposure
D. Out of focus
Answer with the option's letter from the given choices directly.

prompts: [["Which image quality issue does not exist in this image?\nA. Noise\nB. Overexposure\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])
 C.

[Running Accuracy]: 0.7764,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1382:  93%|████████▎| 1383/1495 [08:31<00:34,  3.20it/s]
[Running Accuracy]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1383:  93%|▉| 1383/1495 [08:31<00:34,  3.20it/
 {'prompt': "A chat between 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 not exist in this image?\nA. Noise\nB. Overexposure\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>How is the tone of the grassland in 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 tone of the grassland in the image?
A. Dark
B. Bright
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the tone of the grassland in the image?\nA. Dark\nB. Bright\nC. Medium\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.8125], 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]: 0.7766,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1383:  93%|▉| 1384/1495 [08:31<00:43,  2.53it/
[Running Accuracy]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1384:  93%|███████▍| 1384/1495 [08:31<00:43,  2.53it/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 tone of the grassland in the 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 composition 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 composition of this image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Acceptable\nB. Good\nC. Poor\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]: 0.7760,[Response]: C.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1384:  93%|███████▍| 1385/1495 [08:32<00:41,  2.68it/s]
[Running Accuracy]: 0.7755,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1385:  93%|█▊| 1385/1495 [08:32<00:41,  2.68it/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 composition of this image?\nA. Acceptable\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>How is the contrast level 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 contrast level of this image?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the contrast level of this image?\nA. Low\nB. High\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]: 0.7755,[Response]: B.<|endoftext|>, [Correct Ans]: Acceptable, , [Prog]: 1385:  93%|█▊| 1386/1495 [08:32<00:38,  2.83it/s]
[Running Accuracy]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1386:  93%|████████▎| 1386/1495 [08:32<00:38,  2.83it/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 contrast level 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>What is the degree of blurriness of the image?
A. Some blurriness
B. Completely 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 blurriness
B. Completely 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 blurriness\nB. Completely 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]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1386:  93%|████████▎| 1387/1495 [08:32<00:36,  2.93it/s]
[Running Accuracy]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Some blurriness, , [Prog]: 1387:  93%|▉| 1387/1495 [08:32<00:36,  2.93i
 {'prompt': "A chat between a curious 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 blurriness\nB. Completely 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 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([-30.9219], 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]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Some blurriness, , [Prog]: 1387:  93%|▉| 1388/1495 [08:33<00:35,  3.02i
[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1388:  93%|█████████▎| 1388/1495 [08:33<00:35,  3.02it/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>Is this picture 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 color of the flowers 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 flowers 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 flowers in this image vibrant?\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])
 A.

[Running Accuracy]: 0.7752,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1388:  93%|█████████▎| 1389/1495 [08:33<00:34,  3.04it/s]
[Running Accuracy]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1389:  93%|█████████▎| 1389/1495 [08:33<00:34,  3.04it/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>Is the color of the flowers 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>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([-31.1406], 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]: 0.7754,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1389:  93%|█████████▎| 1390/1495 [08:33<00:33,  3.10it/s]
[Running Accuracy]: 0.7755,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1390:  93%|████████▎| 1390/1495 [08:33<00:33,  3.10it/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>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 color of the flowers in this photo?
A. Monotonous
B. Vibrant
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the color of the flowers in this photo?
A. Monotonous
B. Vibrant
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the color of the flowers in this photo?\nA. Monotonous\nB. Vibrant\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])
 B.

[Running Accuracy]: 0.7755,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1390:  93%|████████▎| 1391/1495 [08:33<00:33,  3.09it/s]
[Running Accuracy]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1391:  93%|████▋| 1391/1495 [08:33<00:33,  3.09it/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 color of the flowers in this photo?\nA. Monotonous\nB. Vibrant\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. 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([-31.1562], 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]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Vibrant, , [Prog]: 1391:  93%|████▋| 1392/1495 [08:34<00:32,  3.12it/s]
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1392:  93%|██████▌| 1392/1495 [08:34<00:32,  3.12it/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 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>What is the most serious quality problem in the image?
A. Blur
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 problem in the image?
A. Blur
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 problem in the image?\nA. Blur\nB. Overexposure\nC. Motion blur\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])
 D.

[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1392:  93%|██████▌| 1393/1495 [08:34<00:34,  2.99it/s]
[Running Accuracy]: 0.7760,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1393:  93%|██████▌| 1393/1495 [08:34<00:34,  2.99it/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>What is the most serious quality problem in the image?\nA. Blur\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>Is the dog the focus of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the dog the focus of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the dog the focus of this picture?\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]: 0.7760,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1393:  93%|██████▌| 1394/1495 [08:35<00:35,  2.88it/s]
[Running Accuracy]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1394:  93%|████████▍| 1394/1495 [08:35<00:35,  2.88it/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>Is the dog the focus 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 this image aesthetically pleasing in terms of composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this image aesthetically pleasing in terms of composition?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this image aesthetically pleasing in terms of composition?\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]: 0.7762,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1394:  93%|████████▍| 1395/1495 [08:35<00:33,  2.99it/s]
[Running Accuracy]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1395:  93%|████████▍| 1395/1495 [08:35<00:33,  2.99it/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>Is this image aesthetically pleasing in terms of 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 kind of feeling does the image convey?
A. Dull
B. Lively
C. Dark
D. Restless
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of feeling does the image convey?
A. Dull
B. Lively
C. Dark
D. Restless
Answer with the option's letter from the given choices directly.

prompts: [["What kind of feeling does the image convey?\nA. Dull\nB. Lively\nC. Dark\nD. Restless\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]: 0.7763,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1395:  93%|████████▍| 1396/1495 [08:35<00:32,  3.04it/s]
[Running Accuracy]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: Lively, , [Prog]: 1396:  93%|█████▌| 1396/1495 [08:35<00:32,  3.04it/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>What kind of feeling does the image convey?\nA. Dull\nB. Lively\nC. Dark\nD. Restless\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 blur is in this image?
A. Glass Blur
B. Motion Blur
C. Defocus Blur
D. Zoom Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of blur is in this image?
A. Glass Blur
B. Motion Blur
C. Defocus Blur
D. Zoom Blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of blur is in this image?\nA. Glass Blur\nB. Motion Blur\nC. Defocus Blur\nD. Zoom 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])
 B.

[Running Accuracy]: 0.7765,[Response]: B.<|endoftext|>, [Correct Ans]: Lively, , [Prog]: 1396:  93%|█████▌| 1397/1495 [08:36<00:40,  2.41it/s]
[Running Accuracy]: 0.7767,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1397:  93%|▉| 1397/1495 [08:36<00:40,  2.41it/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>What kind of blur is in this image?\nA. Glass Blur\nB. Motion Blur\nC. Defocus Blur\nD. Zoom 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>Which part of this image is the clearest?
A. Ground and sky
B. Person
C. Mountain
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which part of this image is the clearest?
A. Ground and sky
B. Person
C. Mountain
Answer with the option's letter from the given choices directly.

prompts: [["Which part of this image is the clearest?\nA. Ground and sky\nB. Person\nC. Mountain\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]: 0.7767,[Response]: B.<|endoftext|>, [Correct Ans]: Motion Blur, , [Prog]: 1397:  94%|▉| 1398/1495 [08:36<00:38,  2.54it/s]
[Running Accuracy]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1398:  94%|█████▌| 1398/1495 [08:36<00:38,  2.54it/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>Which part of this image is the clearest?\nA. Ground and sky\nB. Person\nC. Mountain\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat 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([-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]: 0.7768,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1398:  94%|█████▌| 1399/1495 [08:37<00:43,  2.19it/s]
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1399:  94%|████████▍| 1399/1495 [08:37<00:43,  2.19it/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>Does this picture 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>What is the worst distortion in this picture?
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 is the worst distortion in this picture?
A. Motion blur
B. Overexposure
C. Out of focus
D. 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. Out of focus\nD. Underexposure\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]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1399:  94%|████████▍| 1400/1495 [08:37<00:42,  2.24it/s]
[Running Accuracy]: 0.7771,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1400:  94%|▉| 1400/1495 [08:37<00:42,  2.24it/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>What is the worst distortion in this picture?\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>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([-30.7812], 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]: 0.7771,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1400:  94%|▉| 1401/1495 [08:37<00:38,  2.47it/s
[Running Accuracy]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1401:  94%|████████▍| 1401/1495 [08:37<00:38,  2.47it/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>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 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 is the clarity of 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 this image?\nA. Low\nB. Medium\nC. High\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]: 0.7773,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1401:  94%|████████▍| 1402/1495 [08:38<00:35,  2.60it/s]
[Running Accuracy]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1402:  94%|█████▋| 1402/1495 [08:38<00:35,  2.60it/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 clarity 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>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([-30.7656], 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]: 0.7767,[Response]: C.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1402:  94%|█████▋| 1403/1495 [08:38<00:33,  2.78it/s]
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1403:  94%|█████████▍| 1403/1495 [08:38<00:33,  2.78it/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>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>What is the clearest part of the image?
A. Body
B. Sun
C. Stars
D. Helmet
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part of the image?
A. Body
B. Sun
C. Stars
D. Helmet
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part of the image?\nA. Body\nB. Sun\nC. Stars\nD. Helmet\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]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1403:  94%|█████████▍| 1404/1495 [08:38<00:31,  2.85it/s]
[Running Accuracy]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: Helmet, , [Prog]: 1404:  94%|█████▋| 1404/1495 [08:38<00:31,  2.85it/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>What is the clearest part of the image?\nA. Body\nB. Sun\nC. Stars\nD. Helmet\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Brightness
C. Motion blur
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. Brightness
C. Motion blur
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. Brightness\nC. Motion blur\nD. Underexposure\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])
 A.

[Running Accuracy]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: Helmet, , [Prog]: 1404:  94%|█████▋| 1405/1495 [08:39<00:37,  2.40it/s]
[Running Accuracy]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1405:  94%|▉| 1405/1495 [08:39<00:37,  2.40it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Brightness\nC. Motion 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>How is the lighting 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 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 this image?\nA. Bright\nB. Medium\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])
 B.

[Running Accuracy]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1405:  94%|▉| 1406/1495 [08:39<00:36,  2.44it/s
[Running Accuracy]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1406:  94%|███████▌| 1406/1495 [08:39<00:36,  2.44it/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 lighting of 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 arrangement of elements in this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the arrangement of elements in this image?
A. Medium
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How is the arrangement of elements in this image?\nA. Medium\nB. Good\nC. Poor\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]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: Dark, , [Prog]: 1406:  94%|███████▌| 1407/1495 [08:40<00:33,  2.61it/s]
[Running Accuracy]: 0.7754,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1407:  94%|███████▌| 1407/1495 [08:40<00:33,  2.61it/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 arrangement of elements in this image?\nA. Medium\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 clarity 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 clarity of this image?
A. High
B. Medium
C. Low
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of this image?\nA. High\nB. Medium\nC. Low\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.9219], 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]: 0.7754,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1407:  94%|███████▌| 1408/1495 [08:40<00:33,  2.60it/s]
[Running Accuracy]: 0.7749,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1408:  94%|█████▋| 1408/1495 [08:40<00:33,  2.60it/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 clarity of this 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>Is the composition of this image center-oriented?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image center-oriented?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image center-oriented?\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]: 0.7749,[Response]: A.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1408:  94%|█████▋| 1409/1495 [08:40<00:31,  2.72it/s]
[Running Accuracy]: 0.7750,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1409:  94%|████████▍| 1409/1495 [08:40<00:31,  2.72it/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>Is the composition of this image center-oriented?\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's the worst distortion in this picture?
A. Underexposure
B. Overexposure
C. Out of focus
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. Out of focus
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. Out of focus\nD. Noise\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]: 0.7750,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1409:  94%|████████▍| 1410/1495 [08:41<00:39,  2.17it/s]
[Running Accuracy]: 0.7752,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1410:  94%|▉| 1410/1495 [08:41<00:39,  2.17it/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>What's the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Out of focus\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 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([-31.0781], 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]: 0.7752,[Response]: C.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1410:  94%|▉| 1411/1495 [08:41<00:34,  2.41it/s
[Running Accuracy]: 0.7753,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1411:  94%|███████▌| 1411/1495 [08:41<00:34,  2.41it/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 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>Which of the following quality issues does this image not have?
A. Overexposure
B. Noise
C. Underexposure
D. Blur
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. Noise
C. Underexposure
D. Blur
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. Noise\nC. Underexposure\nD. Blur\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]: 0.7753,[Response]: C.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1411:  94%|███████▌| 1412/1495 [08:42<00:32,  2.57it/s]
[Running Accuracy]: 0.7748,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1412:  94%|▉| 1412/1495 [08:42<00:32,  2.57it/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>Which of the following quality issues does this image not have?\nA. Overexposure\nB. Noise\nC. Underexposure\nD. 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 distortion occurs in this image?
A. Artifacts
B. Overexposure
C. Noise
D. Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which distortion occurs in this image?
A. Artifacts
B. Overexposure
C. Noise
D. Blur
Answer with the option's letter from the given choices directly.

prompts: [["Which distortion occurs in this image?\nA. Artifacts\nB. Overexposure\nC. Noise\nD. 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]: 0.7748,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1412:  95%|▉| 1413/1495 [08:42<00:37,  2.19it/s
[Running Accuracy]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1413:  95%|▉| 1413/1495 [08:42<00:37,  2.19it/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>Which distortion occurs in this image?\nA. Artifacts\nB. Overexposure\nC. Noise\nD. 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 person on the right side of the image bright?
A. Average
B. Darker
C. Brighter
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the person on the right side of the image bright?
A. Average
B. Darker
C. Brighter
Answer with the option's letter from the given choices directly.

prompts: [["Is the person on the right side of the image bright?\nA. Average\nB. Darker\nC. Brighter\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]: 0.7749,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1413:  95%|▉| 1414/1495 [08:43<00:33,  2.39it/s
[Running Accuracy]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Brighter, , [Prog]: 1414:  95%|███▊| 1414/1495 [08:43<00:33,  2.39it/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>Is the person on the right side of the image bright?\nA. Average\nB. Darker\nC. Brighter\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between a curious 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([-31.1094], 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]: 0.7744,[Response]: B.<|endoftext|>, [Correct Ans]: Brighter, , [Prog]: 1414:  95%|███▊| 1415/1495 [08:43<00:31,  2.56it/s]
[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1415:  95%|█████▋| 1415/1495 [08:43<00:31,  2.56it/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 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 is the color saturation of the car 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 car 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 car 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])
 C.

[Running Accuracy]: 0.7739,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1415:  95%|█████▋| 1416/1495 [08:43<00:29,  2.69it/s]
[Running Accuracy]: 0.7733,[Response]: C.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1416:  95%|███████▌| 1416/1495 [08:43<00:29,  2.69it/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 color saturation of the car 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>Which of the following image quality issues does not exist in this image?
A. Out of focus
B. Underexposed
C. Noise
D. Overexposed
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. Out of focus
B. Underexposed
C. Noise
D. Overexposed
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. Out of focus\nB. Underexposed\nC. Noise\nD. Overexposed\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]: Good, , [Prog]: 1416:  95%|███████▌| 1417/1495 [08:44<00:27,  2.81it/s]
[Running Accuracy]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1417:  95%|▉| 1417/1495 [08:44<00:27,  2.81it/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>Which of the following image quality issues does not exist in this image?\nA. Out of focus\nB. Underexposed\nC. Noise\nD. 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>What is the clarity of the tire in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clarity of the tire in this image?
A. Low
B. Medium
C. High
Answer with the option's letter from the given choices directly.

prompts: [["What is the clarity of the tire in this image?\nA. Low\nB. Medium\nC. High\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]: 0.7735,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1417:  95%|▉| 1418/1495 [08:44<00:31,  2.46it/s
[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1418:  95%|████████▌| 1418/1495 [08:44<00:31,  2.46it/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>What is the clarity of the tire 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>What is the clearest part in this image?
A. Pastries
B. Floor
C. Table
D. Plate
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the clearest part in this image?
A. Pastries
B. Floor
C. Table
D. Plate
Answer with the option's letter from the given choices directly.

prompts: [["What is the clearest part in this image?\nA. Pastries\nB. Floor\nC. Table\nD. Plate\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]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1418:  95%|████████▌| 1419/1495 [08:45<00:29,  2.58it/s]
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Pastries, , [Prog]: 1419:  95%|███▊| 1419/1495 [08:45<00:29,  2.58it/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>What is the clearest part in this image?\nA. Pastries\nB. Floor\nC. Table\nD. Plate\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

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

prompts: [["What types of quality problems does the image have?\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([-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]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: Pastries, , [Prog]: 1419:  95%|███▊| 1420/1495 [08:45<00:28,  2.64it/s]
[Running Accuracy]: 0.7732,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1420:  95%|██████▋| 1420/1495 [08:45<00:28,  2.64it/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>What types of quality problems does the image have?\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': '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 robot in the image have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the robot in the image have overexposure issues?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the robot in the image have overexposure issues?\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]: 0.7732,[Response]: D.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1420:  95%|██████▋| 1421/1495 [08:45<00:27,  2.73it/s]
[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1421:  95%|█████████▌| 1421/1495 [08:45<00:27,  2.73it/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>Does the robot in the image 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 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([-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]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1421:  95%|█████████▌| 1422/1495 [08:46<00:26,  2.80it/s]
[Running Accuracy]: 0.7729,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1422:  95%|████████▌| 1422/1495 [08:46<00:26,  2.80it/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>Is the main subject highlighted?\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 image composition, which object is emphasized in the center?
A. Table
B. Carpet
C. Chair
D. Sofa
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. Table
B. Carpet
C. Chair
D. Sofa
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. Table\nB. Carpet\nC. Chair\nD. Sofa\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]: 0.7729,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1422:  95%|████████▌| 1423/1495 [08:46<00:24,  2.93it/s]
[Running Accuracy]: 0.7730,[Response]: D.<|endoftext|>, [Correct Ans]: Sofa, , [Prog]: 1423:  95%|███████▌| 1423/1495 [08:46<00:24,  2.93it/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>In image composition, which object is emphasized in the center?\nA. Table\nB. Carpet\nC. Chair\nD. Sofa\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 tires clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the tires clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Are the tires clear 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])
 A.

[Running Accuracy]: 0.7730,[Response]: D.<|endoftext|>, [Correct Ans]: Sofa, , [Prog]: 1423:  95%|███████▌| 1424/1495 [08:47<00:31,  2.22it/s]
[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1424:  95%|█████████▌| 1424/1495 [08:47<00:31,  2.22it/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>Are the tires 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>Does this image look realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look realistic?\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]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1424:  95%|█████████▌| 1425/1495 [08:47<00:30,  2.33it/s]
[Running Accuracy]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1425:  95%|█████████▌| 1425/1495 [08:47<00:30,  2.33it/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>Does this 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>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([-30.8125], 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]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1425:  95%|█████████▌| 1426/1495 [08:47<00:27,  2.55it/s]
[Running Accuracy]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1426:  95%|███████▋| 1426/1495 [08:47<00:27,  2.55it/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 colorful is this picture?\nA. Dull\nB. Normal\nC. Colorful\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between 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 image give?
A. Gloomy
B. Relaxed
C. Dull
D. Agitated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of visual feeling does the image give?
A. Gloomy
B. Relaxed
C. Dull
D. Agitated
Answer with the option's letter from the given choices directly.

prompts: [["What kind of visual feeling does the image give?\nA. Gloomy\nB. Relaxed\nC. Dull\nD. Agitated\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]: 0.7735,[Response]: A.<|endoftext|>, [Correct Ans]: Dull, , [Prog]: 1426:  95%|███████▋| 1427/1495 [08:48<00:25,  2.71it/s]
[Running Accuracy]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Relaxed, , [Prog]: 1427:  95%|████▊| 1427/1495 [08:48<00:25,  2.71it/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>What kind of visual feeling does the image give?\nA. Gloomy\nB. Relaxed\nC. Dull\nD. Agitated\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 quality of this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you rate the quality of this image?
A. Acceptable
B. Poor
C. Good
Answer with the option's letter from the given choices directly.

prompts: [["How would you rate the quality of this image?\nA. Acceptable\nB. Poor\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]: 0.7737,[Response]: B.<|endoftext|>, [Correct Ans]: Relaxed, , [Prog]: 1427:  96%|████▊| 1428/1495 [08:48<00:29,  2.29it/s]
[Running Accuracy]: 0.7738,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1428:  96%|███████▋| 1428/1495 [08:48<00:29,  2.29it/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 would you rate the quality of 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>How is the clarity 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 clarity of the image?
A. Bad
B. Good
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How is the clarity of the image?\nA. Bad\nB. Good\nC. Fair\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]: 0.7738,[Response]: B.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1428:  96%|███████▋| 1429/1495 [08:48<00:26,  2.49it/s]
[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 1429:  96%|████████▌| 1429/1495 [08:48<00:26,  2.49it/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 clarity of the image?\nA. Bad\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>What is/are the brightest object(s) in this picture?
A. Trees
B. Buildings
C. Cars
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is/are the brightest object(s) in this picture?
A. Trees
B. Buildings
C. Cars
Answer with the option's letter from the given choices directly.

prompts: [["What is/are the brightest object(s) in this picture?\nA. Trees\nB. Buildings\nC. Cars\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]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Bad, , [Prog]: 1429:  96%|████████▌| 1430/1495 [08:49<00:24,  2.66it/s]
[Running Accuracy]: 0.7741,[Response]: C.<|endoftext|>, [Correct Ans]: Cars, , [Prog]: 1430:  96%|███████▋| 1430/1495 [08:49<00:24,  2.66it/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>What is/are the brightest object(s) in this picture?\nA. Trees\nB. Buildings\nC. Cars\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Mountain
B. Person
C. Cloud
D. Sword
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in this image is the focus?
A. Mountain
B. Person
C. Cloud
D. Sword
Answer with the option's letter from the given choices directly.

prompts: [["Which object in this image is the focus?\nA. Mountain\nB. Person\nC. Cloud\nD. Sword\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]: 0.7741,[Response]: C.<|endoftext|>, [Correct Ans]: Cars, , [Prog]: 1430:  96%|███████▋| 1431/1495 [08:49<00:23,  2.78it/s]
[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1431:  96%|█████▋| 1431/1495 [08:49<00:23,  2.78it/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>Which object in this image is the focus?\nA. Mountain\nB. Person\nC. Cloud\nD. Sword\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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 to have the highest saturation?
A. Sky
B. Sea surface
C. Beach
D. Juice
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image appears to have the highest saturation?
A. Sky
B. Sea surface
C. Beach
D. Juice
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image appears to have the highest saturation?\nA. Sky\nB. Sea surface\nC. Beach\nD. Juice\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])
 D.

[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: Person, , [Prog]: 1431:  96%|█████▋| 1432/1495 [08:49<00:21,  2.90it/s]
[Running Accuracy]: 0.7744,[Response]: D.<|endoftext|>, [Correct Ans]: Juice, , [Prog]: 1432:  96%|██████▋| 1432/1495 [08:49<00:21,  2.90it/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>Which object in the image appears to have the highest saturation?\nA. Sky\nB. Sea surface\nC. Beach\nD. Juice\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 color is the most eye-catching in this image?
A. red
B. brown
C. white
D. green
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. red
B. brown
C. white
D. green
Answer with the option's letter from the given choices directly.

prompts: [["Which color is the most eye-catching in this image?\nA. red\nB. brown\nC. white\nD. green\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])
 D.

[Running Accuracy]: 0.7744,[Response]: D.<|endoftext|>, [Correct Ans]: Juice, , [Prog]: 1432:  96%|██████▋| 1433/1495 [08:50<00:20,  2.99it/s]
[Running Accuracy]: 0.7746,[Response]: D.<|endoftext|>, [Correct Ans]: green, , [Prog]: 1433:  96%|██████▋| 1433/1495 [08:50<00:20,  2.99it/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>Which color is the most eye-catching in this image?\nA. red\nB. brown\nC. white\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>What is the worst distortion in this picture?
A. Underexposure
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. Underexposure
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. Underexposure\nB. Overexposure\nC. Noise\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])
 D.

[Running Accuracy]: 0.7746,[Response]: D.<|endoftext|>, [Correct Ans]: green, , [Prog]: 1433:  96%|██████▋| 1434/1495 [08:50<00:19,  3.06it/s]
[Running Accuracy]: 0.7748,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1434:  96%|▉| 1434/1495 [08:50<00:19,  3.06it/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>What is the worst distortion in this picture?\nA. Underexposure\nB. Overexposure\nC. Noise\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>Which object is emphasized in the center in the composition of this image?
A. House
B. Sky
C. Ground
D. Panda
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is emphasized in the center in the composition of this image?
A. House
B. Sky
C. Ground
D. Panda
Answer with the option's letter from the given choices directly.

prompts: [["Which object is emphasized in the center in the composition of this image?\nA. House\nB. Sky\nC. Ground\nD. Panda\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])
 D.

[Running Accuracy]: 0.7748,[Response]: D.<|endoftext|>, [Correct Ans]: Motion blur, , [Prog]: 1434:  96%|▉| 1435/1495 [08:50<00:19,  3.06it/s]
[Running Accuracy]: 0.7749,[Response]: D.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 1435:  96%|██████▋| 1435/1495 [08:50<00:19,  3.06it/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>Which object is emphasized in the center in the composition of this image?\nA. House\nB. Sky\nC. Ground\nD. Panda\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 in the image is heavily affected by motion blur?
A. Wall
B. Window
C. Ground
D. Woman
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object in the image is heavily affected by motion blur?
A. Wall
B. Window
C. Ground
D. Woman
Answer with the option's letter from the given choices directly.

prompts: [["Which object in the image is heavily affected by motion blur?\nA. Wall\nB. Window\nC. Ground\nD. Woman\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])
 D.

[Running Accuracy]: 0.7749,[Response]: D.<|endoftext|>, [Correct Ans]: Panda, , [Prog]: 1435:  96%|██████▋| 1436/1495 [08:51<00:19,  3.10it/s]
[Running Accuracy]: 0.7751,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 1436:  96%|██████▋| 1436/1495 [08:51<00:19,  3.10it/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>Which object in the image is heavily affected by motion blur?\nA. Wall\nB. Window\nC. Ground\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>Does this image look photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look photo-realistic?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look photo-realistic?\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])
 B.

[Running Accuracy]: 0.7751,[Response]: D.<|endoftext|>, [Correct Ans]: Woman, , [Prog]: 1436:  96%|██████▋| 1437/1495 [08:51<00:18,  3.08it/s]
[Running Accuracy]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1437:  96%|█████████▌| 1437/1495 [08:51<00:18,  3.08it/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>Does this image look photo-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 animal the focus in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the animal the focus in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the animal the focus in this 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]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1437:  96%|█████████▌| 1438/1495 [08:51<00:18,  3.10it/s]
[Running Accuracy]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1438:  96%|████████▋| 1438/1495 [08:51<00:18,  3.10it/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>Is the animal the focus 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 exposure of the trees in this picture?
A. Overexposed
B. No exposure-related issues
C. Underexposed
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How's the exposure of the trees in this picture?
A. Overexposed
B. No exposure-related issues
C. Underexposed
Answer with the option's letter from the given choices directly.

prompts: [["How's the exposure of the trees in this picture?\nA. Overexposed\nB. No exposure-related issues\nC. Underexposed\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]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1438:  96%|████████▋| 1439/1495 [08:52<00:20,  2.67it/s]
[Running Accuracy]: 0.7755,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1439:  96%|▉| 1439/1495 [08:52<00:20,  2.67it/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's the exposure of the trees in this picture?\nA. Overexposed\nB. No exposure-related issues\nC. Underexposed\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 suffer from?
A. Overexposure
B. Underexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What kind of distortion does this image suffer from?
A. Overexposure
B. Underexposure
C. Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["What kind of distortion does this image suffer from?\nA. Overexposure\nB. Underexposure\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])
 B.

[Running Accuracy]: 0.7755,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposed, , [Prog]: 1439:  96%|▉| 1440/1495 [08:52<00:19,  2.75it/s
[Running Accuracy]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1440:  96%|▉| 1440/1495 [08:52<00:19,  2.75it/
 {'prompt': "A chat between 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 suffer from?\nA. Overexposure\nB. Underexposure\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 would you describe the overall clarity of the image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How would you describe the overall clarity of the image?
A. Acceptable
B. Good
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How would you describe the overall clarity of the image?\nA. Acceptable\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]: 0.7757,[Response]: B.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1440:  96%|▉| 1441/1495 [08:53<00:23,  2.26it/
[Running Accuracy]: 0.7759,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1441:  96%|███████▋| 1441/1495 [08:53<00:23,  2.26it/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 would you describe the overall clarity of 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>How blurry is 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 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 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([-31.2969], 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]: 0.7759,[Response]: C.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1441:  96%|███████▋| 1442/1495 [08:53<00:21,  2.44it/s]
[Running Accuracy]: 0.7753,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1442:  96%|▉| 1442/1495 [08:53<00:21,  2.44i
 {'prompt': "A chat between 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. Very blurry\nC. Not blurry at all\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

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

prompts: [["How about the calrity of the poster and Chinese characters?\nA. Poor\nB. High\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])
 A.

[Running Accuracy]: 0.7753,[Response]: C.<|endoftext|>, [Correct Ans]: Slightly blurry, , [Prog]: 1442:  97%|▉| 1443/1495 [08:54<00:22,  2.31i
[Running Accuracy]: 0.7755,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1443:  97%|███████▋| 1443/1495 [08:54<00:22,  2.31it/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 about the calrity of the poster and Chinese characters?\nA. Poor\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>Does this image look like it was taken in real life?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image look like it was taken in real life?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image look like it was taken in real life?\nA. No\nB. Yes\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]: 0.7755,[Response]: A.<|endoftext|>, [Correct Ans]: Poor, , [Prog]: 1443:  97%|███████▋| 1444/1495 [08:54<00:20,  2.49it/s]
[Running Accuracy]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1444:  97%|█████████▋| 1444/1495 [08:54<00:20,  2.49it/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>Does this image look like it was taken in real life?\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 image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is the image?
A. Good
B. Average
C. Poor
Answer with the option's letter from the given choices directly.

prompts: [["How clear is the image?\nA. Good\nB. Average\nC. Poor\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]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1444:  97%|█████████▋| 1445/1495 [08:54<00:19,  2.60it/s]
[Running Accuracy]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1445:  97%|███████▋| 1445/1495 [08:54<00:19,  2.60it/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 clear is 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>What is the style of human characters in this image?
A. Impressionism
B. Realistic
C. Animation
D. Sketch-like
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the style of human characters in this image?
A. Impressionism
B. Realistic
C. Animation
D. Sketch-like
Answer with the option's letter from the given choices directly.

prompts: [["What is the style of human characters in this image?\nA. Impressionism\nB. Realistic\nC. Animation\nD. Sketch-like\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]: 0.7758,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1445:  97%|███████▋| 1446/1495 [08:55<00:18,  2.63it/s]
[Running Accuracy]: 0.7759,[Response]: C.<|endoftext|>, [Correct Ans]: Animation, , [Prog]: 1446:  97%|██▉| 1446/1495 [08:55<00:18,  2.63it/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>What is the style of human characters in this image?\nA. Impressionism\nB. Realistic\nC. Animation\nD. Sketch-like\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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. Fair
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How clear is this picture?
A. Blurry
B. Clear
C. Fair
Answer with the option's letter from the given choices directly.

prompts: [["How clear is this picture?\nA. Blurry\nB. Clear\nC. Fair\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]: 0.7759,[Response]: C.<|endoftext|>, [Correct Ans]: Animation, , [Prog]: 1446:  97%|██▉| 1447/1495 [08:56<00:25,  1.89it/s]
[Running Accuracy]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1447:  97%|██████▊| 1447/1495 [08:56<00:25,  1.89it/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 clear is 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 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([-30.8594], 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]: 0.7761,[Response]: B.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1447:  97%|██████▊| 1448/1495 [08:56<00:21,  2.15it/s]
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1448:  97%|█████████▋| 1448/1495 [08:56<00:21,  2.15it/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>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 worst distortion in this picture?
A. Underexposure
B. Out of focus
C. Motion blur
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. Underexposure
B. Out of focus
C. Motion blur
D. Overexposure
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\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])
 B.

[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1448:  97%|█████████▋| 1449/1495 [08:56<00:24,  1.91it/s]
[Running Accuracy]: 0.7764,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1449:  97%|▉| 1449/1495 [08:57<00:24,  1.91it/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>What is the worst distortion in this picture?\nA. Underexposure\nB. Out of focus\nC. Motion blur\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>Does this picture have strong motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have strong motion blur?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have strong motion blur?\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]: 0.7764,[Response]: B.<|endoftext|>, [Correct Ans]: Out of focus, , [Prog]: 1449:  97%|▉| 1450/1495 [08:57<00:20,  2.17it/s
[Running Accuracy]: 0.7766,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1450:  97%|████████▋| 1450/1495 [08:57<00:20,  2.17it/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>Does this picture have strong 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>Where is the focus of this picture?
A. Center
B. Upper left corner
C. Lower right corner
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Where is the focus of this picture?
A. Center
B. Upper left corner
C. Lower right corner
Answer with the option's letter from the given choices directly.

prompts: [["Where is the focus of this picture?\nA. Center\nB. Upper left corner\nC. Lower right corner\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]: 0.7766,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1450:  97%|████████▋| 1451/1495 [08:57<00:18,  2.41it/s]
[Running Accuracy]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 1451:  97%|█████▊| 1451/1495 [08:57<00:18,  2.41it/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>Where is the focus of this picture?\nA. Center\nB. Upper left corner\nC. Lower right corner\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat 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 photo-realistic, computer-generated, or sketch-like?
A. Photo-realistic
B. Sketch-like
C. Computer-generated
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the image look photo-realistic, computer-generated, or sketch-like?
A. Photo-realistic
B. Sketch-like
C. Computer-generated
Answer with the option's letter from the given choices directly.

prompts: [["Does the image look photo-realistic, computer-generated, or sketch-like?\nA. Photo-realistic\nB. Sketch-like\nC. Computer-generated\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-31.6562], 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]: 0.7767,[Response]: A.<|endoftext|>, [Correct Ans]: Center, , [Prog]: 1451:  97%|█████▊| 1452/1495 [08:58<00:20,  2.14it/s]
[Running Accuracy]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1452:  97%|▉| 1452/1495 [08:58<00:20,  2.14i
 {'prompt': "A chat 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 photo-realistic, computer-generated, or sketch-like?\nA. Photo-realistic\nB. Sketch-like\nC. 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>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([-31.3750], 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]: 0.7769,[Response]: A.<|endoftext|>, [Correct Ans]: Photo-realistic, , [Prog]: 1452:  97%|▉| 1453/1495 [08:58<00:17,  2.37i
[Running Accuracy]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1453:  97%|█████████▋| 1453/1495 [08:58<00:17,  2.37it/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>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>What is the main light source in the image?
A. Reflected light
B. Streetlight
C. Sunlight
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the main light source in the image?
A. Reflected light
B. Streetlight
C. Sunlight
Answer with the option's letter from the given choices directly.

prompts: [["What is the main light source in the image?\nA. Reflected light\nB. Streetlight\nC. Sunlight\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]: 0.7770,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1453:  97%|█████████▋| 1454/1495 [08:58<00:16,  2.52it/s]
[Running Accuracy]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 1454:  97%|███▉| 1454/1495 [08:58<00:16,  2.52it/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>What is the main light source in the image?\nA. Reflected light\nB. Streetlight\nC. Sunlight\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 

prompt A chat between 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 building in this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What do you think of the lighting of the building in this image?
A. Bright
B. Dark
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["What do you think of the lighting of the building in this image?\nA. Bright\nB. Dark\nC. Medium\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]: 0.7772,[Response]: C.<|endoftext|>, [Correct Ans]: Sunlight, , [Prog]: 1454:  97%|███▉| 1455/1495 [08:59<00:15,  2.66it/s]
[Running Accuracy]: 0.7766,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1455:  97%|█████▊| 1455/1495 [08:59<00:15,  2.66it/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>What do you think of the lighting of the building in this 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>Is the woman on the right of the image clear?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the woman on the right of the image clear?
A. Clear
B. Not clear
Answer with the option's letter from the given choices directly.

prompts: [["Is the woman on the right of the image clear?\nA. Clear\nB. Not clear\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]: 0.7766,[Response]: B.<|endoftext|>, [Correct Ans]: Medium, , [Prog]: 1455:  97%|█████▊| 1456/1495 [08:59<00:14,  2.68it/s]
[Running Accuracy]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1456:  97%|██████▊| 1456/1495 [08:59<00:14,  2.68it/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>Is the woman on the right of the image clear?\nA. Clear\nB. Not 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 color of the 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 image vivid?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the color of the image vivid?\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]: 0.7768,[Response]: A.<|endoftext|>, [Correct Ans]: Clear, , [Prog]: 1456:  97%|██████▊| 1457/1495 [08:59<00:13,  2.83it/s]
[Running Accuracy]: 0.7763,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1457:  97%|████████▊| 1457/1495 [08:59<00:13,  2.83it/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>Is the color of the 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>Is the human standing in the middle of the image blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the human standing in the middle of the image blurry?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the human standing in the middle of the image blurry?\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]: 0.7763,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1457:  98%|████████▊| 1458/1495 [09:00<00:12,  2.90it/s]
[Running Accuracy]: 0.7757,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1458:  98%|████████▊| 1458/1495 [09:00<00:12,  2.90it/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>Is the human standing in the middle of the 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>Does the wall contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does the wall contain rich texture?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Does the wall contain rich texture?\nA. Yes\nB. No\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])
 A.

[Running Accuracy]: 0.7757,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1458:  98%|████████▊| 1459/1495 [09:01<00:17,  2.03it/s]
[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1459:  98%|████████▊| 1459/1495 [09:01<00:17,  2.03it/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>Does the wall contain rich 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 color style of the image?
A. Reddish
B. Yellowish
C. Grayish
D. Blueish
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the color style of the image?
A. Reddish
B. Yellowish
C. Grayish
D. Blueish
Answer with the option's letter from the given choices directly.

prompts: [["What is the color style of the image?\nA. Reddish\nB. Yellowish\nC. Grayish\nD. Blueish\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])
 D.

[Running Accuracy]: 0.7759,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1459:  98%|████████▊| 1460/1495 [09:01<00:15,  2.25it/s]
[Running Accuracy]: 0.7760,[Response]: D.<|endoftext|>, [Correct Ans]: Blueish, , [Prog]: 1460:  98%|████▉| 1460/1495 [09:01<00:15,  2.25it/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>What is the color style of the image?\nA. Reddish\nB. Yellowish\nC. Grayish\nD. Blueish\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 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([-31.0781], 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]: 0.7760,[Response]: D.<|endoftext|>, [Correct Ans]: Blueish, , [Prog]: 1460:  98%|████▉| 1461/1495 [09:01<00:14,  2.40it/s]
[Running Accuracy]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1461:  98%|████████▊| 1461/1495 [09:01<00:14,  2.40it/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>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>Is the image blurry due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the image blurry due to movement?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the image blurry due to movement?\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]: 0.7762,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1461:  98%|████████▊| 1462/1495 [09:02<00:12,  2.57it/s]
[Running Accuracy]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1462:  98%|█████████▊| 1462/1495 [09:02<00:12,  2.57it/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>Is the image blurry 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 color of the flowers 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 flowers 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 flowers in this 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]: 0.7756,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1462:  98%|█████████▊| 1463/1495 [09:02<00:11,  2.69it/s]
[Running Accuracy]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1463:  98%|████████▊| 1463/1495 [09:02<00:11,  2.69it/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>Is the color of the flowers 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 the composition of this image pyramid-like?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the composition of this image pyramid-like?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the composition of this image pyramid-like?\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])
 A.

[Running Accuracy]: 0.7758,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1463:  98%|████████▊| 1464/1495 [09:02<00:11,  2.79it/s]
[Running Accuracy]: 0.7760,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1464:  98%|█████████▊| 1464/1495 [09:02<00:11,  2.79it/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>Is the composition of this image pyramid-like?\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 composition of this image is emphasized in the center?
A. Car
B. Walking man
C. Trees
D. Trash bin
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. Car
B. Walking man
C. Trees
D. Trash bin
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. Car\nB. Walking man\nC. Trees\nD. Trash bin\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]: 0.7760,[Response]: A.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1464:  98%|█████████▊| 1465/1495 [09:03<00:10,  2.82it/s]
[Running Accuracy]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Trash bin, , [Prog]: 1465:  98%|██▉| 1465/1495 [09:03<00:10,  2.82it/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>Which object in the composition of this image is emphasized in the center?\nA. Car\nB. Walking man\nC. Trees\nD. Trash bin\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'B.<|endoftext|>'} 

prompt A chat between 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. Strong
B. Weak
C. No 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. Strong
B. Weak
C. No Motion Blur
Answer with the option's letter from the given choices directly.

prompts: [["How severe is the motion blur in this image?\nA. Strong\nB. Weak\nC. No Motion Blur\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]: 0.7754,[Response]: B.<|endoftext|>, [Correct Ans]: Trash bin, , [Prog]: 1465:  98%|██▉| 1466/1495 [09:03<00:12,  2.40it/s]
[Running Accuracy]: 0.7749,[Response]: A.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 1466:  98%|███████▊| 1466/1495 [09:03<00:12,  2.40it/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 severe is the motion blur in this image?\nA. Strong\nB. Weak\nC. No 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 color saturation of the player's clothing high in the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the color saturation of the player's clothing high in the image?
A. High
B. Low
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["Is the color saturation of the player's clothing high in the image?\nA. High\nB. Low\nC. Medium\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]: 0.7749,[Response]: A.<|endoftext|>, [Correct Ans]: Weak, , [Prog]: 1466:  98%|███████▊| 1467/1495 [09:03<00:11,  2.53it/s]
[Running Accuracy]: 0.7751,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1467:  98%|███████▊| 1467/1495 [09:03<00:11,  2.53it/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>Is the color saturation of the player's clothing high 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>How blurry is the small cat in the image?
A. Very blurry
B. Not blurry at all
C. Slightly blurry
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How blurry is the small cat in the image?
A. Very blurry
B. Not blurry at all
C. Slightly blurry
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the small cat in the image?\nA. Very blurry\nB. Not blurry at all\nC. Slightly blurry\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]: 0.7751,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1467:  98%|███████▊| 1468/1495 [09:04<00:10,  2.64it/s]
[Running Accuracy]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1468:  98%|▉| 1468/1495 [09:04<00:10,  2.6
 {'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>How blurry is the small cat in the image?\nA. Very blurry\nB. Not blurry at all\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>How blurry is the image?
A. Very blurry
B. Not blurry at all
C. Slightly 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. Slightly 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. Slightly 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])
 C.

[Running Accuracy]: 0.7752,[Response]: B.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1468:  98%|▉| 1469/1495 [09:04<00:09,  2.7
[Running Accuracy]: 0.7747,[Response]: C.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1469:  98%|▉| 1469/1495 [09:04<00:09,  2.7
 {'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>How blurry is the image?\nA. Very blurry\nB. Not blurry at all\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 cup at bottom left over-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the cup at bottom left over-exposed?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the cup at bottom left over-exposed?\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]: 0.7747,[Response]: C.<|endoftext|>, [Correct Ans]: Not blurry at all, , [Prog]: 1469:  98%|▉| 1470/1495 [09:04<00:08,  2.8
[Running Accuracy]: 0.7748,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1470:  98%|████████▊| 1470/1495 [09:04<00:08,  2.82it/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>Is the cup at bottom left over-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>Does this image have high rendering accuracy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this image have high rendering accuracy?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this image have high rendering accuracy?\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]: 0.7748,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1470:  98%|████████▊| 1471/1495 [09:05<00:08,  2.80it/s]
[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1471:  98%|█████████▊| 1471/1495 [09:05<00:08,  2.80it/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>Does this image have high rendering accuracy?\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. 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. 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. Motion 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])
 C.

[Running Accuracy]: 0.7743,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1471:  98%|█████████▊| 1472/1495 [09:05<00:07,  2.94it/s]
[Running Accuracy]: 0.7745,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1472:  98%|██████▉| 1472/1495 [09:05<00:07,  2.94it/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>What is the worst distortion in this picture?\nA. Out of focus\nB. Motion blur\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 the focus in this image?
A. The ground
B. The sheep eating grass
C. The sheep not eating grass
D. The grass
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Which object is the focus in this image?
A. The ground
B. The sheep eating grass
C. The sheep not eating grass
D. The grass
Answer with the option's letter from the given choices directly.

prompts: [["Which object is the focus in this image?\nA. The ground\nB. The sheep eating grass\nC. The sheep not eating grass\nD. The grass\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]: 0.7745,[Response]: C.<|endoftext|>, [Correct Ans]: Noise, , [Prog]: 1472:  99%|██████▉| 1473/1495 [09:05<00:07,  2.92it/s]
[Running Accuracy]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: The sheep not eating grass, , [Prog]: 1473:  99%|▉| 1473/1495 [09:05<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>Which object is the focus in this image?\nA. The ground\nB. The sheep eating grass\nC. The sheep not eating grass\nD. The 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 people 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
Is the people emphasized in the center of this picture?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the people 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([-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]: 0.7739,[Response]: A.<|endoftext|>, [Correct Ans]: The sheep not eating grass, , [Prog]: 1473:  99%|▉| 1474/1495 [09:06<00
[Running Accuracy]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1474:  99%|████████▊| 1474/1495 [09:06<00:07,  2.98it/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>Is the people 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': 'B.<|endoftext|>'} 

prompt A chat 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 three people standing at the doorway in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Are the three people standing at the doorway in this image clear?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Are the three people standing at the doorway in this image clear?\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]: 0.7741,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1474:  99%|████████▉| 1475/1495 [09:06<00:06,  2.98it/s]
[Running Accuracy]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1475:  99%|█████████▊| 1475/1495 [09:06<00:06,  2.98it/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>Are the three people standing at the doorway 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 composition of this image?
A. Good
B. Bad
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the composition of this image?
A. Good
B. Bad
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the composition of this image?\nA. Good\nB. Bad\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]: 0.7742,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1475:  99%|█████████▊| 1476/1495 [09:06<00:06,  3.08it/s]
[Running Accuracy]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1476:  99%|███████▉| 1476/1495 [09:06<00:06,  3.08it/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 composition of this image?\nA. Good\nB. Bad\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>Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Does this picture have noise?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Does this picture have noise?\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]: 0.7744,[Response]: A.<|endoftext|>, [Correct Ans]: Good, , [Prog]: 1476:  99%|███████▉| 1477/1495 [09:07<00:05,  3.06it/s]
[Running Accuracy]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1477:  99%|████████▉| 1477/1495 [09:07<00:05,  3.06it/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>Does this picture 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 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([-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]: 0.7745,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1477:  99%|████████▉| 1478/1495 [09:07<00:05,  3.13it/s]
[Running Accuracy]: 0.7747,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1478:  99%|████████▉| 1478/1495 [09:07<00:05,  3.13it/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>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': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Green
B. White
C. Gray
D. Black
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest color in this image?
A. Green
B. White
C. Gray
D. Black
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest color in this image?\nA. Green\nB. White\nC. Gray\nD. Black\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]: Yes, , [Prog]: 1478:  99%|████████▉| 1479/1495 [09:07<00:05,  3.07it/s]
[Running Accuracy]: 0.7742,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 1479:  99%|██████▉| 1479/1495 [09:07<00:05,  3.07it/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>What is the brightest color in this image?\nA. Green\nB. White\nC. Gray\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 of the following quality issues does not exist in this image?
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 quality issues does not exist in this image?
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 quality issues does not exist in this image?\nA. Noise\nB. Underexposure\nC. Out of focus\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n"]]
alpha tensor([-30.0938], 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]: 0.7742,[Response]: C.<|endoftext|>, [Correct Ans]: Green, , [Prog]: 1479:  99%|██████▉| 1480/1495 [09:08<00:04,  3.12it/s]
[Running Accuracy]: 0.7736,[Response]: B.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1480:  99%|▉| 1480/1495 [09:08<00:04,  3.12it/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>Which of the following quality issues does not exist in this image?\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>In image composition, which object is emphasized in the center?
A. ship
B. white building
C. black building
D. stone
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. ship
B. white building
C. black building
D. stone
Answer with the option's letter from the given choices directly.

prompts: [["In image composition, which object is emphasized in the center?\nA. ship\nB. white building\nC. black building\nD. stone\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]: Overexposure, , [Prog]: 1480:  99%|▉| 1481/1495 [09:08<00:04,  3.10it/s
[Running Accuracy]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: ship, , [Prog]: 1481:  99%|███████▉| 1481/1495 [09:08<00:04,  3.10it/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>In image composition, which object is emphasized in the center?\nA. ship\nB. white building\nC. black building\nD. stone\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'A.<|endoftext|>'} 

prompt A chat between a curious 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. Sky
B. Buildings
C. River
D. Trees
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What is the brightest part in this picture?
A. Sky
B. Buildings
C. River
D. Trees
Answer with the option's letter from the given choices directly.

prompts: [["What is the brightest part in this picture?\nA. Sky\nB. Buildings\nC. River\nD. Trees\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]: 0.7738,[Response]: A.<|endoftext|>, [Correct Ans]: ship, , [Prog]: 1481:  99%|███████▉| 1482/1495 [09:09<00:05,  2.49it/s]
[Running Accuracy]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1482:  99%|████████▉| 1482/1495 [09:09<00:05,  2.49it/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>What is the brightest part in this picture?\nA. Sky\nB. Buildings\nC. River\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>Is the main part of the fried egg in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main part of the fried egg in focus?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the main part of the fried egg in focus?\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]: 0.7740,[Response]: A.<|endoftext|>, [Correct Ans]: Sky, , [Prog]: 1482:  99%|████████▉| 1483/1495 [09:09<00:04,  2.61it/s]
[Running Accuracy]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1483:  99%|█████████▉| 1483/1495 [09:09<00:04,  2.61it/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>Is the main part of the fried egg 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 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([-31.1094], 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]: 0.7734,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1483:  99%|█████████▉| 1484/1495 [09:10<00:04,  2.30it/s]
[Running Accuracy]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1484:  99%|████████▉| 1484/1495 [09:10<00:04,  2.30it/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>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 color saturation of 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 color saturation of the image?
A. Good
B. Moderate
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. Moderate\nC. Poor\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]: 0.7736,[Response]: A.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1484:  99%|████████▉| 1485/1495 [09:10<00:03,  2.53it/s]
[Running Accuracy]: 0.7731,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1485:  99%|███▉| 1485/1495 [09:10<00:03,  2.53it/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 color saturation of the image?\nA. Good\nB. Moderate\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 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 the 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 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]: 0.7731,[Response]: C.<|endoftext|>, [Correct Ans]: Moderate, , [Prog]: 1485:  99%|███▉| 1486/1495 [09:10<00:03,  2.70it/s]
[Running Accuracy]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1486:  99%|███████▉| 1486/1495 [09:10<00:03,  2.70it/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 color saturation of 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>Which of the following image quality issues does not exist in this picture?
A. Underexposure
B. Overexposure
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 issues does not exist in this picture?
A. Underexposure
B. Overexposure
C. Out of focus
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. Underexposure\nB. Overexposure\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]: 0.7732,[Response]: A.<|endoftext|>, [Correct Ans]: High, , [Prog]: 1486:  99%|███████▉| 1487/1495 [09:10<00:02,  2.84it/s]
[Running Accuracy]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1487:  99%|▉| 1487/1495 [09:10<00:02,  2.84it/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>Which of the following image quality issues does not exist in this picture?\nA. Underexposure\nB. Overexposure\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 texture sharpness of the cattle?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
How is the texture sharpness of the cattle?
A. Low
B. High
C. Medium
Answer with the option's letter from the given choices directly.

prompts: [["How is the texture sharpness of the cattle?\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]: 0.7727,[Response]: A.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1487: 100%|▉| 1488/1495 [09:11<00:02,  2.93it/s
[Running Accuracy]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1488: 100%|████████▉| 1488/1495 [09:11<00:02,  2.93it/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 texture sharpness of the cattle?\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>Is the main subject well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the main subject well-defined?
A. Yes
B. No
Answer with the option's letter from the given choices directly.

prompts: [["Is the main subject well-defined?\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]: 0.7728,[Response]: A.<|endoftext|>, [Correct Ans]: Low, , [Prog]: 1488: 100%|████████▉| 1489/1495 [09:11<00:01,  3.05it/s]
[Running Accuracy]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1489: 100%|█████████▉| 1489/1495 [09:11<00:01,  3.05it/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>Is the main subject well-defined?\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 aesthetically pleasing in terms of composition
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is this picture aesthetically pleasing in terms of composition
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is this picture aesthetically pleasing in terms of composition\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]: 0.7730,[Response]: B.<|endoftext|>, [Correct Ans]: No, , [Prog]: 1489: 100%|█████████▉| 1490/1495 [09:11<00:01,  3.03it/s]
[Running Accuracy]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1490: 100%|████████▉| 1490/1495 [09:11<00:01,  3.03it/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>Is this picture aesthetically pleasing in terms of 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 yak clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
Is the yak clear in this image?
A. No
B. Yes
Answer with the option's letter from the given choices directly.

prompts: [["Is the yak clear 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]: 0.7732,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1490: 100%|████████▉| 1491/1495 [09:12<00:01,  3.01it/s]
[Running Accuracy]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1491: 100%|████████▉| 1491/1495 [09:12<00:01,  3.01it/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>Is the yak 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 is the worst distortion in this image?
A. Sharpness
B. Brightness
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 image?
A. Sharpness
B. Brightness
C. Underexposure
D. Motion blur
Answer with the option's letter from the given choices directly.

prompts: [["What is the worst distortion in this image?\nA. Sharpness\nB. Brightness\nC. Underexposure\nD. Motion blur\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]: 0.7733,[Response]: B.<|endoftext|>, [Correct Ans]: Yes, , [Prog]: 1491: 100%|████████▉| 1492/1495 [09:12<00:01,  2.45it/s]
[Running Accuracy]: 0.7728,[Response]: D.<|endoftext|>, [Correct Ans]: Sharpness, , [Prog]: 1492: 100%|██▉| 1492/1495 [09:12<00:01,  2.45it/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>What is the worst distortion in this image?\nA. Sharpness\nB. Brightness\nC. Underexposure\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>How blurry is 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 image?
A. Moderate
B. Severe
C. Slight
Answer with the option's letter from the given choices directly.

prompts: [["How blurry is the image?\nA. Moderate\nB. Severe\nC. Slight\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]: 0.7728,[Response]: D.<|endoftext|>, [Correct Ans]: Sharpness, , [Prog]: 1492: 100%|██▉| 1493/1495 [09:13<00:00,  2.63it/s]
[Running Accuracy]: 0.7729,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1493: 100%|█████▉| 1493/1495 [09:13<00:00,  2.63it/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 blurry is 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>What problem does the image not have?
A. Overexposure
B. Backlighting
C. Motion blur
D. Underexposure
Answer with the option's letter from the given choices directly.
 ASSISTANT:
using prompts
What problem does the image not have?
A. Overexposure
B. Backlighting
C. Motion blur
D. Underexposure
Answer with the option's letter from the given choices directly.

prompts: [["What problem does the image not have?\nA. Overexposure\nB. Backlighting\nC. Motion blur\nD. Underexposure\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]: 0.7729,[Response]: B.<|endoftext|>, [Correct Ans]: Severe, , [Prog]: 1493: 100%|█████▉| 1494/1495 [09:13<00:00,  2.77it/s]
[Running Accuracy]: 0.7724,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1494: 100%|▉| 1494/1495 [09:13<00:00,  2.77it/
 {'prompt': "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: <image>What problem does the image not have?\nA. Overexposure\nB. Backlighting\nC. Motion blur\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>Which of the following image quality issues does not exist in this image?
A. Blur
B. Noise
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 not exist in this image?
A. Blur
B. Noise
C. Underexposure
D. Overexposure
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. Blur\nB. Noise\nC. Underexposure\nD. Overexposure\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]: 0.7724,[Response]: C.<|endoftext|>, [Correct Ans]: Underexposure, , [Prog]: 1494: 100%|█| 1495/1495 [09:13<00:00,  2.89it/
[Running Accuracy]: 0.7719,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1495: 100%|█| 1495/1495 [09:13<00:00,  2.89it/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>Which of the following image quality issues does not exist in this image?\nA. Blur\nB. Noise\nC. Underexposure\nD. Overexposure\nAnswer with the option's letter from the given choices directly.\n ASSISTANT:", 'outputs': 'C.<|endoftext|>'} 


[Running Accuracy]: 0.7719,[Response]: C.<|endoftext|>, [Correct Ans]: Overexposure, , [Prog]: 1495: 100%|█| 1495/1495 [09:13<00:00,  2.70it/s