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Hi,
I am attempting to fine-tune a model with Vietnamese characters using the configuration provided below. I updated DICT90 to include 219 characters, as follows:
DICT90 = tuple('AÁÀẠẢÃĂẮẰẲẶẴÂẤẦẨẪẬBCDĐEÈÉẼẺẸÊẾỀỂỄỆFGHIÍÌỈĨỊJKLMNOPQRSTUVWXYZ'
'aáàạảãăằắẳẵặâấầẩẫậbcdđeèéẻẽẹêếềểễệfghiíìỉĩịjklmnopqrstuvwxyz'
'0123456789!"#$%&\'()*+,-./:;<=>?@[\\]_~') # 219 charactersHere is my CCD_vision_model_ARD.yaml configuration:
global:
name: finetune_small_65536_1
phase: train
stage: train-supervised
workdir: workdir
seed: ~
output_dir: './saved_models/'
dataset:
scheme: supervised
type: ST
train: {
roots: [
'./Dino/data_lmdb/training',
],
batch_size: 8,
}
valid: {
roots: [
'./Dino/data_lmdb/validation'
],
batch_size: 8
}
test: {
roots: [
'./Dino/data_lmdb/evaluation'
],
batch_size: 14
}
data_aug: True
multiscales: False
mask: False
num_workers: 6
augmentation_severity: 0
charset_path: './Dino/data/charset_vi.txt' # Vietnamese charset
charset_type: 'DICT90' # Changed to Vietnamese charset in base.py
training:
epochs: 20
start_iters: 0
show_iters: 1000
eval_iters: 1000
save_iters: 1000
model:
pretrain_checkpoint: 'saved_models/Small_ARD_checkpoint.pth'
checkpoint:
decoder:
type: 'NRTRDecoder'
n_layers: 6
d_embedding: 512
n_head: 8
d_model: 512
d_inner: 256
d_k: 64
d_v: 64
num_classes: 221 # 219 + 2
max_seq_len: 25
start_idx: 220 # 219 + 1
padding_idx: 221 # 219 + 2
mp:
num: 4
arch: 'vit_small'
patch_size: 4
out_dim: 65536
weight_decay: 0.05
clip_grad: ~
lr: 0.0005
warmup_epochs: 2
min_lr: 0.000001
optimizer: adamw
drop_path_rate: 0.1
seed: 0
num_workers: 8After running finetune.py, the model's accuracy is only 0. I am unsure if there is an error in the configuration or if something else might be wrong.
Could you please help me identify if there is any mistake in the setup or configuration? Any guidance or suggestions would be greatly appreciated.
Thanks.
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