Edit model card

vit-xray-pneumonia-classification

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:

  • Loss: 0.0740
  • Accuracy: 0.9734

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4843 0.9882 63 0.1954 0.9408
0.1986 1.9922 127 0.1483 0.9494
0.1694 2.9961 191 0.1316 0.9459
0.1368 4.0 255 0.1207 0.9554
0.1399 4.9882 318 0.1738 0.9296
0.1203 5.9922 382 0.0966 0.9631
0.1085 6.9961 446 0.0956 0.9631
0.1046 8.0 510 0.0952 0.9665
0.0883 8.9882 573 0.0990 0.9665
0.0773 9.9922 637 0.0896 0.9717
0.0815 10.9961 701 0.1084 0.9605
0.0793 12.0 765 0.0767 0.9742
0.0778 12.9882 828 0.0885 0.9691
0.0609 13.9922 892 0.0778 0.9708
0.0685 14.8235 945 0.0740 0.9734

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0
  • Datasets 2.19.0
  • Tokenizers 0.19.1
Downloads last month
5
Safetensors
Model size
85.8M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Larbz-7/vit-xray-pneumonia-classification

Finetuned
(1670)
this model