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vit-diabetic-retinopathy-classification – AI Model by Kontawat | AlphaNeural AI
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Kontawat
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vit-diabetic-retinopathy-classification
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-diabetic-retinopathy-classification
This model is a fine-tuned version of
Kontawat/vit-diabetic-retinopathy-classification
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0460
Accuracy: 0.7287
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: 0.0002
train_batch_size: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5645
0.94
100
0.7731
0.7239
0.3971
1.89
200
0.8123
0.7038
0.3239
2.83
300
0.8204
0.7239
0.2178
3.77
400
0.9085
0.7204
0.18
4.72
500
1.0284
0.7310
0.0501
5.66
600
1.0460
0.7287
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.0
Tokenizers 0.13.2
