Getting training error

[noobbuddy]

From past 27 days I am trying to fix my Lora error, but no matters what methods I use, I even use chat got, but still it´s didn't fix. So please if someone knows how to correct that error please let me know (sorry for my bad english).

Folder 75_test: 11 images found
Folder 75_test: 825 steps
max_train_steps = 825
stop_text_encoder_training = 0
lr_warmup_steps = 82
accelerate launch --num_cpu_threads_per_process=2 "train_network.py" --enable_bucket --pretrained_model_name_or_path="D:/stable-diffusion/stable-diffusion-webui/models/Stable-diffusion/anything-v4.0-pruned.ckpt" --train_data_dir="D:/stable-diffusion/output/image" --resolution=512,512 --output_dir="D:/stable-diffusion/output/model" --logging_dir="D:/stable-diffusion/output/log" --network_alpha="1" --save_model_as=safetensors --network_module=networks.lora --text_encoder_lr=5e-5 --unet_lr=0.0001 --network_dim=8 --output_name="last" --lr_scheduler_num_cycles="1" --learning_rate="0.0001" --lr_scheduler="cosine" --lr_warmup_steps="82" --train_batch_size="1" --max_train_steps="825" --save_every_n_epochs="1" --mixed_precision="fp16" --save_precision="fp16" --cache_latents --optimizer_type="AdamW8bit" --max_data_loader_n_workers="0" --bucket_reso_steps=64 --xformers --bucket_no_upscale
prepare tokenizer
Use DreamBooth method.
prepare images.
found directory D:\stable-diffusion\output\image\75_test contains 22 image files
1650 train images with repeating.
0 reg images.
no regularization images / 正則化画像が見つかりませんでした
[Dataset 0]
  batch_size: 1
  resolution: (512, 512)
  enable_bucket: True
  min_bucket_reso: 256
  max_bucket_reso: 1024
  bucket_reso_steps: 64
  bucket_no_upscale: True

  [Subset 0 of Dataset 0]
    image_dir: "D:\stable-diffusion\output\image\75_test"
    image_count: 22
    num_repeats: 75
    shuffle_caption: False
    keep_tokens: 0
    caption_dropout_rate: 0.0
    caption_dropout_every_n_epoches: 0
    caption_tag_dropout_rate: 0.0
    color_aug: False
    flip_aug: False
    face_crop_aug_range: None
    random_crop: False
    is_reg: False
    class_tokens: test
    caption_extension: .caption


[Dataset 0]
loading image sizes.
100%|██████████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<00:00, 77.78it/s]
make buckets
min_bucket_reso and max_bucket_reso are ignored if bucket_no_upscale is set, because bucket reso is defined by image size automatically / bucket_no_upscaleが指定された場合は、bucketの解像度は画像サイズから自動計算されるため、min_bucket_resoとmax_bucket_resoは無視されます
number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）
bucket 0: resolution (384, 640), count: 75
bucket 1: resolution (512, 320), count: 75
bucket 2: resolution (512, 448), count: 75
bucket 3: resolution (512, 512), count: 600
mean ar error (without repeats): 0.0284594653226946
prepare accelerator
Using accelerator 0.15.0 or above.
load StableDiffusion checkpoint
loading u-net: <All keys matched successfully>
loading vae: <All keys matched successfully>
Traceback (most recent call last):
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\transformers\modeling_utils.py", line 415, in load_state_dict
    return torch.load(checkpoint_file, map_location="cpu")
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\torch\serialization.py", line 705, in load
    with _open_zipfile_reader(opened_file) as opened_zipfile:
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\torch\serialization.py", line 242, in __init__
    super(_open_zipfile_reader, self).__init__(torch._C.PyTorchFileReader(name_or_buffer))
RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\transformers\modeling_utils.py", line 419, in load_state_dict
    if f.read(7) == "version":
  File "D:\python\lib\encodings\cp1252.py", line 23, in decode
    return codecs.charmap_decode(input,self.errors,decoding_table)[0]
UnicodeDecodeError: 'charmap' codec can't decode byte 0x81 in position 2077: character maps to <undefined>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:\stable-diffusion\kohya\kohya_ss\train_network.py", line 699, in <module>
    train(args)
  File "D:\stable-diffusion\kohya\kohya_ss\train_network.py", line 126, in train
    text_encoder, vae, unet, _ = train_util.load_target_model(args, weight_dtype)
  File "D:\stable-diffusion\kohya\kohya_ss\library\train_util.py", line 2545, in load_target_model
    text_encoder, vae, unet = model_util.load_models_from_stable_diffusion_checkpoint(args.v2, name_or_path)
  File "D:\stable-diffusion\kohya\kohya_ss\library\model_util.py", line 921, in load_models_from_stable_diffusion_checkpoint
    text_model = CLIPTextModel.from_pretrained("openai/clip-vit-large-patch14")
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\transformers\modeling_utils.py", line 2301, in from_pretrained
    state_dict = load_state_dict(resolved_archive_file)
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\transformers\modeling_utils.py", line 431, in load_state_dict
    raise OSError(
OSError: Unable to load weights from pytorch checkpoint file for 'C:\Users\bisha/.cache\huggingface\hub\models--openai--clip-vit-large-patch14\snapshots\8d052a0f05efbaefbc9e8786ba291cfdf93e5bff\pytorch_model.bin' at 'C:\Users\bisha/.cache\huggingface\hub\models--openai--clip-vit-large-patch14\snapshots\8d052a0f05efbaefbc9e8786ba291cfdf93e5bff\pytorch_model.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
Traceback (most recent call last):
  File "D:\python\lib\runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "D:\python\lib\runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "D:\stable-diffusion\kohya\kohya_ss\venv\Scripts\accelerate.exe\__main__.py", line 7, in <module>
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\accelerate_cli.py", line 45, in main
    args.func(args)
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 1104, in launch_command
    simple_launcher(args)
  File "D:\stable-diffusion\kohya\kohya_ss\venv\lib\site-packages\accelerate\commands\launch.py", line 567, in simple_launcher
    raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['D:\\stable-diffusion\\kohya\\kohya_ss\\venv\\Scripts\\python.exe', 'train_network.py', '--enable_bucket', '--pretrained_model_name_or_path=D:/stable-diffusion/stable-diffusion-webui/models/Stable-diffusion/anything-v4.0-pruned.ckpt', '--train_data_dir=D:/stable-diffusion/output/image', '--resolution=512,512', '--output_dir=D:/stable-diffusion/output/model', '--logging_dir=D:/stable-diffusion/output/log', '--network_alpha=1', '--save_model_as=safetensors', '--network_module=networks.lora', '--text_encoder_lr=5e-5', '--unet_lr=0.0001', '--network_dim=8', '--output_name=last', '--lr_scheduler_num_cycles=1', '--learning_rate=0.0001', '--lr_scheduler=cosine', '--lr_warmup_steps=82', '--train_batch_size=1', '--max_train_steps=825', '--save_every_n_epochs=1', '--mixed_precision=fp16', '--save_precision=fp16', '--cache_latents', '--optimizer_type=AdamW8bit', '--max_data_loader_n_workers=0', '--bucket_reso_steps=64', '--xformers', '--bucket_no_upscale']' returned non-zero exit status 1.