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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-pneumonia-classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/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
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