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BEiT-finetuned – AI Model by jadohu | AlphaNeural AI
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BEiT-finetuned
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transformers
pytorch
tensorboard
beit
image-classification
generated_from_trainer
cifar10
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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BEiT-finetuned
This model is a fine-tuned version of
microsoft/beit-base-patch16-224
on the cifar10 dataset. It achieves the following results on the evaluation set:
Loss: 0.0256
Accuracy: 0.9918
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: 3e-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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3296
1.0
351
0.0492
0.9862
0.2353
2.0
702
0.0331
0.9894
0.2127
3.0
1053
0.0256
0.9918
Framework versions
Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.1
Tokenizers 0.12.1
