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vit-base-beans – AI Model by nateraw | AlphaNeural AI
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nateraw
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vit-base-beans
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
en
beans
apache-2.0
model-index
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: 0.0942
Accuracy: 0.9774
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: 8
eval_batch_size: 8
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2809
1.0
130
0.2287
0.9699
0.1097
2.0
260
0.1676
0.9624
0.1027
3.0
390
0.0942
0.9774
0.0923
4.0
520
0.1104
0.9699
0.1726
5.0
650
0.1030
0.9699
Framework versions
Transformers 4.10.0.dev0
Pytorch 1.9.0+cu102
Datasets 1.11.1.dev0
Tokenizers 0.10.3
