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vit-base-ham10000 – AI Model by PREMAADC | AlphaNeural AI
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PREMAADC
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vit-base-ham10000
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transformers
safetensors
vit
image-classification
skin-lesion
dermatology
generated_from_trainer
google/vit-base-patch16-224
finetune
apache-2.0
endpoints_compatible
us
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vit-base-ham10000
This model is a fine-tuned version of
google/vit-base-patch16-224
on the HAM10000 dataset. It achieves the following results on the evaluation set:
Loss: 0.5809
Accuracy: 0.7848
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: 0.0003
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6898
1.0
501
0.6788
0.7474
0.5914
2.0
1002
0.6237
0.7664
0.6228
3.0
1503
0.6005
0.7763
0.5843
4.0
2004
0.5855
0.7848
0.5569
5.0
2505
0.5809
0.7848
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
