amiguel/mri_classifier

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

• Train Loss: 0.0075
• Validation Loss: 0.0023
• Train Accuracy: 1.0
• Epoch: 14

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:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.1501	0.0619	0.9845	0
0.0524	0.0825	0.9733	1
0.0324	0.1416	0.9494	2
0.0243	0.0327	0.9887	3
0.0258	0.0095	0.9986	4
0.0166	0.0069	0.9986	5
0.0342	0.0126	0.9958	6
0.0131	0.0057	0.9986	7
0.0120	0.0037	0.9986	8
0.0163	0.0055	0.9972	9
0.0083	0.0018	1.0	10
0.0128	0.0027	0.9986	11
0.0070	0.0020	1.0	12
0.0083	0.0014	1.0	13
0.0075	0.0023	1.0	14

Framework versions

• Transformers 4.42.4
• TensorFlow 2.15.0
• Datasets 2.20.0
• Tokenizers 0.19.1