metadata

license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - chest-xray-classification
metrics:
  - accuracy
model-index:
  - name: vit-pneumonia-classification
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: chest-xray-classification
          type: chest-xray-classification
          config: full
          split: validation
          args: full
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9560951680156978

vit-pneumonia-classification

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

Loss: 0.1301
Accuracy: 0.9561

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4786	1.0	32	0.3081	0.8609
0.213	2.0	64	0.1645	0.9399
0.1724	3.0	96	0.1419	0.9502
0.1438	4.0	128	0.0950	0.9734
0.1267	5.0	160	0.1225	0.9579

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.0