---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google/vit-base-patch16-224-in21k
datasets:
- medmnist-v2
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: pneumoniamnist-vit-base-finetuned
  results: []
---

<!-- 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. -->

# pneumoniamnist-vit-base-finetuned

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 medmnist-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1773
- Accuracy: 0.9359
- Precision: 0.9474
- Recall: 0.9179
- F1: 0.9295

## 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: 0.005
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2447        | 0.9898 | 73   | 0.1538          | 0.9351   | 0.9013    | 0.9466 | 0.9200 |
| 0.3466        | 1.9932 | 147  | 0.2451          | 0.9122   | 0.9197    | 0.8466 | 0.8750 |
| 0.2074        | 2.9966 | 221  | 0.1711          | 0.9427   | 0.9538    | 0.8961 | 0.9203 |
| 0.1928        | 4.0    | 295  | 0.1044          | 0.9618   | 0.9482    | 0.9525 | 0.9503 |
| 0.2043        | 4.9898 | 368  | 0.1007          | 0.9580   | 0.9491    | 0.9403 | 0.9446 |
| 0.1717        | 5.9932 | 442  | 0.0930          | 0.9618   | 0.9432    | 0.9598 | 0.9510 |
| 0.1498        | 6.9966 | 516  | 0.0845          | 0.9637   | 0.9448    | 0.9635 | 0.9536 |
| 0.1531        | 8.0    | 590  | 0.1661          | 0.9332   | 0.8974    | 0.9526 | 0.9188 |
| 0.1451        | 8.9898 | 663  | 0.0760          | 0.9637   | 0.9464    | 0.9611 | 0.9534 |
| 0.1263        | 9.8983 | 730  | 0.0824          | 0.9580   | 0.9355    | 0.9596 | 0.9466 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1