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swin-tiny-patch4-window7-224-fraud_number_classification-fraud_number_classification – AI Model by 100rab25 | AlphaNeural AI
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100rab25
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swin-tiny-patch4-window7-224-fraud_number_classification-fraud_number_classification
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transformers
tensorboard
safetensors
swin
image-classification
generated_from_trainer
imagefolder
100rab25/swin-tiny-patch4-window7-224-fraud_number_classification
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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swin-tiny-patch4-window7-224-fraud_number_classification-fraud_number_classification
This model is a fine-tuned version of
100rab25/swin-tiny-patch4-window7-224-fraud_number_classification
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0010
Accuracy: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0444
1.0
70
0.0041
0.9990
0.0418
2.0
140
0.0063
0.9990
0.022
3.0
210
0.0018
0.9990
0.0226
4.0
280
0.0010
1.0
0.013
5.0
350
0.0009
1.0
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
