metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: vit-xray-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: 0.9742489270386266
vit-xray-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: 0.0868
- Accuracy: 0.9742
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5152 | 0.99 | 63 | 0.2507 | 0.9245 |
| 0.2334 | 1.99 | 127 | 0.1766 | 0.9382 |
| 0.1647 | 3.0 | 191 | 0.1218 | 0.9588 |
| 0.144 | 4.0 | 255 | 0.1222 | 0.9502 |
| 0.1348 | 4.99 | 318 | 0.1293 | 0.9571 |
| 0.1276 | 5.99 | 382 | 0.1000 | 0.9665 |
| 0.1175 | 7.0 | 446 | 0.1177 | 0.9502 |
| 0.109 | 8.0 | 510 | 0.1079 | 0.9665 |
| 0.0914 | 8.99 | 573 | 0.0804 | 0.9717 |
| 0.0872 | 9.99 | 637 | 0.0800 | 0.9717 |
| 0.0804 | 11.0 | 701 | 0.0862 | 0.9682 |
| 0.0935 | 12.0 | 765 | 0.0883 | 0.9657 |
| 0.0686 | 12.99 | 828 | 0.0868 | 0.9742 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.9.0+cu102
- Datasets 2.12.0
- Tokenizers 0.13.3