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food-vit-tutorial – AI Model by spolivin | AlphaNeural AI
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spolivin
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food-vit-tutorial
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transformers
tensorboard
onnx
safetensors
vit
image-classification
generated_from_trainer
food101
google/vit-base-patch16-224-in21k
quantized
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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food-vit-tutorial
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on food101 dataset. It achieves the following results on the evaluation set:
Loss: 1.0267
Accuracy: 0.916
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
2.7889
0.99
62
2.5577
0.838
1.7142
2.0
125
1.6126
0.879
1.2887
2.99
187
1.2513
0.903
1.0307
4.0
250
1.0673
0.922
1.0022
4.96
310
1.0267
0.916
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
