set mixed_precision="fp16",but the model is not fp16

### Describe the bug

I trained the control net of SDXL using the mixed prediction="fp16" parameter, but the trained model did not have the suffix. fp16. safetensors. But it's a 5G file. I see that the Controlnet on HuggFace will have a 5G file and a 2.5G file with fp16.

### Reproduction

accelerate launch train_controlnet_sdxl.py --pretrained_model_name_or_path=$MODEL_DIR --output_dir=$OUTPUT_DIR --pretrained_vae_model_name_or_path=$VAE --dataset_name=/root/autodl-tmp/datasets/ --mixed_precision="fp16" --resolution=1024 --learning_rate=1e-5 --max_train_steps=20000 --validation_image "/root/test.jpg" --validation_prompt "bedroom" --validation_steps=500 --train_batch_size=2 --gradient_accumulation_steps=4 --report_to="wandb" --seed=42 --checkpointing_steps=2000 --cache_dir=/root/autodl-tmp/cache/

### Logs

_No response_

### System Info

diffuser 0.28 , linux, python 3.10.11

### Who can help?

_No response_

从 train_controlnet_sdxl.py 和提供的 accelerate launch 命令开始，然后跟踪 mixed_precision="fp16" 如何影响训练和检查点保存。将生成的 safetensors 工件与预期的 fp16 文件和完整大小文件进行比较；只有在对报告的文件大小和 dtype 行为有确认的解释或可复现的修复后，才算完成。

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