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HF_CVcourse_FoodClassifier – AI Model by Moreza009 | AlphaNeural AI
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Moreza009
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HF_CVcourse_FoodClassifier
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transformers
tensorboard
safetensors
swin
image-classification
generated_from_trainer
en
microsoft/swin-tiny-patch4-window7-224
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of
microsoft/swin-tiny-patch4-window7-224
on
ethz/food101
dataset. It achieves the following results on the evaluation set:
Loss: 0.9383
Accuracy: 0.7506
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: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.3766
0.9986
532
1.1204
0.7072
1.2542
1.9972
1064
0.9383
0.7506
Framework versions
Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
