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selmamalak/
blood-vit-base-finetuned

peft

safetensors

generated_from_trainer

medmnist-v2

google/vit-base-patch16-224-in21k

adapter

apache-2.0

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blood-vit-base-finetuned

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the medmnist-v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.0692
Accuracy: 0.9790
Precision: 0.9772
Recall: 0.9785
F1: 0.9778

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: 0.005
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.4059	1.0	187	0.1878	0.9311	0.9132	0.9328	0.9201
0.3796	2.0	374	0.2729	0.9083	0.9131	0.8875	0.8861
0.424	3.0	561	0.3701	0.8668	0.8797	0.8520	0.8492
0.3141	4.0	748	0.1849	0.9381	0.9267	0.9336	0.9283
0.2553	5.0	935	0.1075	0.9644	0.9630	0.9612	0.9617
0.2686	6.0	1122	0.1679	0.9486	0.9561	0.9437	0.9489
0.2556	7.0	1309	0.0934	0.9661	0.9651	0.9599	0.9619
0.1777	8.0	1496	0.0835	0.9696	0.9697	0.9683	0.9686
0.1607	9.0	1683	0.0739	0.9772	0.9733	0.9792	0.9759
0.1898	10.0	1870	0.0627	0.9790	0.9764	0.9812	0.9786

Framework versions

PEFT 0.9.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

selmamalak/blood-vit-base-finetuned

blood-vit-base-finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

selmamalak/
blood-vit-base-finetuned