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vit-base-beans – AI Model by VSIPhan | AlphaNeural AI
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VSIPhan
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vit-base-beans
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transformers
tensorboard
safetensors
vit
image-classification
vision
generated_from_trainer
google/vit-base-patch16-224-in21k
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-base-beans
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on the beans dataset. It achieves the following results on the evaluation set:
Loss: 0.1063
Accuracy: 0.9850
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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 1337
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: 5.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4646
1.0
65
0.3753
0.9624
0.206
2.0
130
0.1795
0.9850
0.176
3.0
195
0.1307
0.9774
0.1446
4.0
260
0.1063
0.9850
0.1107
5.0
325
0.1176
0.9774
Framework versions
Transformers 4.55.4
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4
