This model is a fine-tuned version of facebook/convnext-base-224-22k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.2657
Accuracy: 0.8990

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8641	0.9877	20	0.5798	0.8014
0.3857	1.9753	40	0.3247	0.8850
0.2798	2.9630	60	0.2657	0.8990

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

gulsmyigit/convnext-base-224-22k-finetuned-Brain-Tumor-Classification

convnext-base-224-22k-finetuned-Brain-Tumor-Classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gulsmyigit/
convnext-base-224-22k-finetuned-Brain-Tumor-Classification