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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- chestxrayclassification
metrics:
- accuracy
model-index:
- name: pneumonia-classification-model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: chestxrayclassification
type: chestxrayclassification
config: full
split: train
args: full
metrics:
- name: Accuracy
type: accuracy
value: 0.9656862745098039
---
<!-- 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. -->
# pneumonia-classification-model
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 chestxrayclassification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1143
- Accuracy: 0.9657
## 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: 32
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6297 | 0.98 | 25 | 0.5258 | 0.7230 |
| 0.3781 | 2.0 | 51 | 0.3011 | 0.9154 |
| 0.2268 | 2.98 | 76 | 0.1981 | 0.9314 |
| 0.1827 | 4.0 | 102 | 0.1602 | 0.9473 |
| 0.1765 | 4.98 | 127 | 0.1446 | 0.9461 |
| 0.1508 | 6.0 | 153 | 0.1449 | 0.9510 |
| 0.1332 | 6.98 | 178 | 0.1510 | 0.9375 |
| 0.1187 | 8.0 | 204 | 0.1169 | 0.9596 |
| 0.131 | 8.98 | 229 | 0.1315 | 0.9559 |
| 0.1043 | 10.0 | 255 | 0.1114 | 0.9571 |
| 0.1022 | 10.98 | 280 | 0.1633 | 0.9375 |
| 0.0893 | 12.0 | 306 | 0.1167 | 0.9596 |
| 0.0848 | 12.98 | 331 | 0.0936 | 0.9694 |
| 0.0885 | 14.0 | 357 | 0.1074 | 0.9608 |
| 0.0928 | 14.98 | 382 | 0.1052 | 0.9645 |
| 0.0776 | 16.0 | 408 | 0.1116 | 0.9608 |
| 0.0895 | 16.98 | 433 | 0.1060 | 0.9645 |
| 0.0817 | 18.0 | 459 | 0.1107 | 0.9632 |
| 0.0766 | 18.98 | 484 | 0.0993 | 0.9669 |
| 0.0697 | 20.0 | 510 | 0.0938 | 0.9681 |
| 0.0626 | 20.98 | 535 | 0.1199 | 0.9620 |
| 0.0665 | 22.0 | 561 | 0.1100 | 0.9657 |
| 0.0613 | 22.98 | 586 | 0.1246 | 0.9620 |
| 0.054 | 24.0 | 612 | 0.1066 | 0.9645 |
| 0.0474 | 24.98 | 637 | 0.1100 | 0.9669 |
| 0.0456 | 26.0 | 663 | 0.1118 | 0.9645 |
| 0.0473 | 26.98 | 688 | 0.1137 | 0.9645 |
| 0.0543 | 28.0 | 714 | 0.0955 | 0.9632 |
| 0.0493 | 28.98 | 739 | 0.1300 | 0.9559 |
| 0.043 | 30.0 | 765 | 0.1229 | 0.9669 |
| 0.039 | 30.98 | 790 | 0.1125 | 0.9608 |
| 0.0398 | 31.37 | 800 | 0.1143 | 0.9657 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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