vit-384-tongue-image-segmented-augmented – AI Model by e1010101 | AlphaNeural AI

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e1010101/
vit-384-tongue-image-segmented-augmented

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image-classification

generated_from_trainer

google/vit-base-patch16-384

autotrain_compatible

endpoints_compatible

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segmented-augmented

This model is a fine-tuned version of google/vit-base-patch16-384 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5815
Precision: 0.8308
Recall: 0.9136
F1: 0.8703

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.081	1.0	327	0.3693	0.8464	0.8970	0.8710
0.0151	2.0	654	0.4906	0.8171	0.8904	0.8521
0.0066	3.0	981	0.5194	0.8416	0.9003	0.8700
0.0029	4.0	1308	0.5671	0.8308	0.9136	0.8703
0.0026	5.0	1635	0.5815	0.8308	0.9136	0.8703

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1