metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: vit-pneumonia
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: 0.976824034334764
vit-pneumonia
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: 0.1086
- Accuracy: 0.9768
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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0357 | 1.0 | 192 | 0.0955 | 0.9691 |
| 0.0404 | 2.0 | 384 | 0.0720 | 0.9751 |
| 0.0546 | 3.0 | 576 | 0.2275 | 0.9468 |
| 0.0113 | 4.0 | 768 | 0.1386 | 0.9648 |
| 0.0101 | 5.0 | 960 | 0.1212 | 0.9708 |
| 0.0003 | 6.0 | 1152 | 0.0929 | 0.9777 |
| 0.0002 | 7.0 | 1344 | 0.1051 | 0.9777 |
| 0.0002 | 8.0 | 1536 | 0.1075 | 0.9777 |
| 0.0002 | 9.0 | 1728 | 0.1084 | 0.9768 |
| 0.0002 | 10.0 | 1920 | 0.1086 | 0.9768 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2