hiera-finetuned-brain-cancer-mri-dataset-pmram-raw

This model is a fine-tuned version of BTX24/hiera-finetuned-brain-cancer-mri-dataset on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0067
• Accuracy: 1.0
• F1: 1.0
• Precision: 1.0
• Recall: 1.0

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: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine_with_restarts
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 48
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.3437	5.2632	100	0.1688	0.9701	0.9701	0.9721	0.9701
0.0947	10.5263	200	0.0468	0.9834	0.9833	0.9837	0.9834
0.0496	15.7895	300	0.0337	0.9934	0.9934	0.9935	0.9934
0.0389	21.0526	400	0.0067	1.0	1.0	1.0	1.0
0.0243	26.3158	500	0.0036	1.0	1.0	1.0	1.0
0.0137	31.5789	600	0.0146	0.9934	0.9933	0.9934	0.9934
0.0109	36.8421	700	0.0022	1.0	1.0	1.0	1.0
0.0103	42.1053	800	0.0020	1.0	1.0	1.0	1.0
0.0096	47.3684	900	0.0020	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.53.0
• Pytorch 2.7.1+cu126
• Datasets 3.6.0
• Tokenizers 0.21.2