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testing dataset ok; trainer.py take effects

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HT
2025-07-11 11:08:51 +08:00
parent 185959cf2a
commit cfa52e5f2e
11 changed files with 167 additions and 97 deletions
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trainer/saved_models/en_filtered/best_accuracy.pth Normal file
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trainer/saved_models/en_filtered/best_norm_ED.pth Normal file
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trainer/saved_models/en_filtered/log_dataset.txt
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@@ -1,102 +1,30 @@
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dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
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dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
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dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
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dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data/en_sample
opt.select_data: ['all_data/en_sample/train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data/
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data/ dataset[0]: train
dataset_root: all_data dataset: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
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Total_batch_size: 32 = 32
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dataset_root: all_data/valid dataset: /
sub-directory: /. num samples: 194
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--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset[0]: train
dataset_root: all_data dataset: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset[0]: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset[0]: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset[0]: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset[0]: train
sub-directory: /train num samples: 688
num total samples of train: 688 x 1.0 (total_data_usage_ratio) = 688
num samples of train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
dataset_root: all_data/valid dataset: /
sub-directory: /. num samples: 194
--------------------------------------------------------------------------------

9
trainer/saved_models/en_filtered/log_train.txt Normal file
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@@ -0,0 +1,9 @@
[5/300] Train loss: 28.86501, Valid loss: 21.44183, Elapsed_time: 3.73978
Current_accuracy : 0.000, Current_norm_ED : 0.0445
Best_accuracy : 0.000, Best_norm_ED : 0.0445
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Ground Truth | Prediction | Confidence Score & T/F
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"Karjalan outcrop ""Sven""" | eee | 0.0000 False
ESPN Modernize | ee | 0.0000 False
--------------------------------------------------------------------------------

92
trainer/saved_models/en_filtered/opt.txt Normal file
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@@ -0,0 +1,92 @@
------------ Options -------------
number: 0123456789
symbol: !"#$%&'()*+,-./:;<=>?@[\]^_`{|}~ €
lang_char: ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
experiment_name: en_filtered
train_data: all_data
valid_data: all_data/valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 300
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 64
imgW: 600
rgb: False
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: None
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 1
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~ €ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
num_class: 97
---------------------------------------
------------ Options -------------
number: 0123456789
symbol: !"#$%&'()*+,-./:;<=>?@[\]^_`{|}~ €
lang_char: ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
experiment_name: en_filtered
train_data: all_data
valid_data: all_data/valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 300
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 64
imgW: 600
rgb: False
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: None
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 1
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~ €ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
num_class: 97
---------------------------------------