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selmamalak/
organc-vit-base-finetuned

Name: organc-vit-base-finetuned
Availability: InStock

peft

safetensors

generated_from_trainer

medmnist-v2

google/vit-base-patch16-224-in21k

adapter

apache-2.0

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organc-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: 0.2248
Accuracy: 0.9283
Precision: 0.9231
Recall: 0.9160
F1: 0.9189

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
0.6907	1.0	203	0.2221	0.9202	0.9165	0.8691	0.8480
0.5616	2.0	406	0.1278	0.9720	0.9657	0.9694	0.9666
0.5515	3.0	609	0.1428	0.9649	0.9626	0.9640	0.9621
0.4941	4.0	813	0.1016	0.9724	0.9683	0.9696	0.9683
0.4764	5.0	1016	0.0998	0.9716	0.9654	0.9649	0.9637
0.4599	6.0	1219	0.0941	0.9758	0.9775	0.9788	0.9778
0.4525	7.0	1422	0.0861	0.9795	0.9812	0.9793	0.9800
0.3835	8.0	1626	0.0788	0.9849	0.9846	0.9850	0.9847
0.2767	9.0	1829	0.0935	0.9774	0.9805	0.9800	0.9798
0.299	9.99	2030	0.0701	0.9854	0.9843	0.9864	0.9852

Framework versions

PEFT 0.10.0
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

selmamalak/organc-vit-base-finetuned

organc-vit-base-finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

selmamalak/
organc-vit-base-finetuned