---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
datasets:
- medmnist-v2
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: pneumoniamnist-beit-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-beit-base-finetuned

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the medmnist-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3960
- Accuracy: 0.8446
- Precision: 0.8354
- Recall: 0.8312
- F1: 0.8332

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5947        | 0.9898 | 73   | 0.5165          | 0.7424   | 0.3712    | 0.5    | 0.4261 |
| 0.4888        | 1.9932 | 147  | 0.3450          | 0.8569   | 0.8116    | 0.8190 | 0.8151 |
| 0.4022        | 2.9966 | 221  | 0.4225          | 0.8340   | 0.7914    | 0.8567 | 0.8079 |
| 0.4319        | 4.0    | 295  | 0.3600          | 0.8588   | 0.8123    | 0.8589 | 0.8292 |
| 0.3836        | 4.9898 | 368  | 0.3665          | 0.8511   | 0.8054    | 0.8610 | 0.8233 |
| 0.3887        | 5.9932 | 442  | 0.3667          | 0.8645   | 0.8197    | 0.8749 | 0.8383 |
| 0.3947        | 6.9966 | 516  | 0.3951          | 0.8531   | 0.8098    | 0.8744 | 0.8283 |
| 0.3741        | 8.0    | 590  | 0.3449          | 0.8683   | 0.8229    | 0.8678 | 0.8398 |
| 0.3964        | 8.9898 | 663  | 0.3625          | 0.8588   | 0.8128    | 0.8638 | 0.8305 |
| 0.3845        | 9.8983 | 730  | 0.3569          | 0.8569   | 0.8111    | 0.8649 | 0.8292 |


### Framework versions

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