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Fraunhofer_Classical_binary_unbalaced – AI Model by ricardoSLabs | AlphaNeural AI
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Fraunhofer_Classical_binary_unbalaced
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tensorboard
safetensors
beit
generated_from_trainer
imagefolder
microsoft/beit-base-patch16-224-pt22k-ft22k
finetune
apache-2.0
model-index
us
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Fraunhofer_Classical_binary_unbalaced
This model is a fine-tuned version of
microsoft/beit-base-patch16-224-pt22k-ft22k
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0206
Accuracy: 0.9925
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0583
1.0
146
0.0540
0.9784
0.04
2.0
292
0.0524
0.9794
0.023
3.0
438
0.0346
0.9891
0.0181
4.0
584
0.0260
0.9911
0.0193
5.0
730
0.0206
0.9925
Framework versions
Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1
