vit-brain-tumour-v2

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the essam24/brain-tumour-v2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5359
• Accuracy: 0.8704

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1236	0.5128	100	0.5990	0.8481
0.1695	1.0256	200	0.5359	0.8704
0.0186	1.5385	300	0.5705	0.8975
0.0368	2.0513	400	0.6136	0.8975
0.0036	2.5641	500	0.6122	0.9012
0.0029	3.0769	600	0.6067	0.9025
0.0027	3.5897	700	0.6449	0.9025

Framework versions

• Transformers 4.42.4
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1