This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0600
Accuracy: 0.9765

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: 0.0005
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
lr_scheduler_warmup_ratio: 0.5
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1531	0.99	93	0.1351	0.9506
0.2389	1.99	187	0.1534	0.9344
0.2517	3.0	281	0.1484	0.9402
0.1769	4.0	375	0.1108	0.9570
0.0764	4.96	465	0.0600	0.9765

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

ALM-AHME/beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled

beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ALM-AHME/
beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled