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results – AI Model by Reyga | AlphaNeural AI
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Reyga
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
imagefolder
nateraw/vit-age-classifier
finetune
model-index
autotrain_compatible
endpoints_compatible
us
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This model is a fine-tuned version of
nateraw/vit-age-classifier
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0824
Accuracy: 0.9875
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
100
1.5403
0.5375
No log
2.0
200
0.7882
0.725
No log
3.0
300
0.2481
0.9875
No log
4.0
400
0.1088
0.9875
0.8658
5.0
500
0.0824
0.9875
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1
