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deit-small-patch16-224-finetuned-MUSCIMApp – AI Model by nadimkanazi | AlphaNeural AI
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nadimkanazi
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deit-small-patch16-224-finetuned-MUSCIMApp
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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deit-small-patch16-224-finetuned-MUSCIMApp
This model is a fine-tuned version of
facebook/deit-small-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3384
Accuracy: 0.8743
Precision: 0.8675
Recall: 0.8743
F1 Score: 0.8584
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
Precision
Recall
F1 Score
0.3723
1.0
563
0.3915
0.8646
0.8512
0.8646
0.8453
0.3147
2.0
1126
0.3384
0.8743
0.8675
0.8743
0.8584
Framework versions
Transformers 4.30.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.13.3
