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selmamalak/
beit-base-patch16-224-pt22k-ft22k-bloodmnist-fold-9

Name: beit-base-patch16-224-pt22k-ft22k-bloodmnist-fold-9
Availability: InStock

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beit-base-patch16-224-pt22k-ft22k-bloodmnist-fold-9

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the medmnist-v2 dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 0.005
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.4378	1.0	196	0.3362	0.8832	0.8867	0.8308	0.8397
0.4365	2.0	392	0.2239	0.9166	0.9065	0.8995	0.9002
0.4177	3.0	588	0.2136	0.9271	0.9187	0.9164	0.9119
0.3754	4.0	784	0.1673	0.9377	0.9334	0.9216	0.9252
0.4166	5.0	980	0.1747	0.9403	0.9308	0.9374	0.9316
0.2902	6.0	1176	0.1498	0.9447	0.9384	0.9359	0.9352
0.2336	7.0	1372	0.1150	0.9605	0.9563	0.9540	0.9539
0.2198	8.0	1568	0.1307	0.9526	0.9414	0.9566	0.9475
0.1926	9.0	1764	0.0908	0.9675	0.9626	0.9653	0.9638
0.1333	10.0	1960	0.0828	0.9719	0.9682	0.9728	0.9704