vit-msn-small-wbc-classifier-cells-separated-dataset-no-agregates-10

This model is a fine-tuned version of facebook/vit-msn-small on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.1504
• Accuracy: 0.9463

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3353	0.9937	118	0.2299	0.9214
0.2884	1.9958	237	0.2378	0.9172
0.2487	2.9979	356	0.1871	0.9360
0.2347	4.0	475	0.1920	0.9328
0.2343	4.9937	593	0.1674	0.9405
0.2285	5.9958	712	0.1642	0.9426
0.2079	6.9979	831	0.1836	0.9344
0.2155	8.0	950	0.1661	0.9442
0.1954	8.9937	1068	0.1504	0.9463
0.1763	9.9368	1180	0.1588	0.9450

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.2.0
• Tokenizers 0.19.1