---
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: 0.3312
- Accuracy: 0.8878
- Precision: 0.9217
- Recall: 0.8513
- F1: 0.8712

## 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   | 0.1180          | 0.9561   | 0.9313    | 0.9608 | 0.9446 |
| 0.2136        | 1.9932 | 147  | 0.1015          | 0.9637   | 0.9498    | 0.9562 | 0.9529 |
| 0.1431        | 2.9966 | 221  | 0.0729          | 0.9752   | 0.9732    | 0.9615 | 0.9672 |
| 0.1576        | 4.0    | 295  | 0.0873          | 0.9637   | 0.9480    | 0.9586 | 0.9532 |
| 0.2072        | 4.9898 | 368  | 0.0761          | 0.9714   | 0.9616    | 0.9638 | 0.9627 |
| 0.1908        | 5.9932 | 442  | 0.1044          | 0.9599   | 0.9348    | 0.9682 | 0.9496 |
| 0.1637        | 6.9966 | 516  | 0.0742          | 0.9676   | 0.9512    | 0.9661 | 0.9583 |
| 0.1385        | 8.0    | 590  | 0.1843          | 0.9313   | 0.8947    | 0.9537 | 0.9169 |
| 0.1335        | 8.9898 | 663  | 0.0677          | 0.9752   | 0.9626    | 0.9736 | 0.9680 |
| 0.1186        | 9.8983 | 730  | 0.0765          | 0.9752   | 0.9626    | 0.9736 | 0.9680 |


### Framework versions

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