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image_age_classification – AI Model by dini-r-a | AlphaNeural AI
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dini-r-a
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image_age_classification
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transformers
pytorch
vit
image-classification
generated_from_trainer
fair_face
nateraw/vit-age-classifier
finetune
model-index
autotrain_compatible
endpoints_compatible
us
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image_age_classification
This model is a fine-tuned version of
nateraw/vit-age-classifier
on the fair_face dataset. It achieves the following results on the evaluation set:
Loss: 0.9464
Accuracy: 0.601
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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
0.9107
1.0
125
0.9360
0.6065
0.7945
2.0
250
0.9545
0.588
1.0256
3.0
375
1.0144
0.586
0.7354
4.0
500
0.9726
0.594
0.6979
5.0
625
0.9735
0.5995
Framework versions
Transformers 4.34.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.14.5
Tokenizers 0.12.1
