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fruit_veg_detection – AI Model by ammardaffa | AlphaNeural AI
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ammardaffa
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fruit_veg_detection
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transformers
pytorch
vit
image-classification
generated_from_trainer
google/vit-base-patch16-224-in21k
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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fruit_veg_detection
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6689
Accuracy: 0.9116
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: 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
87
0.8126
0.8913
No log
2.0
174
0.6689
0.9116
No log
3.0
261
0.5979
0.9087
No log
4.0
348
0.5629
0.9116
No log
5.0
435
0.5583
0.9014
Framework versions
Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.0
