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

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the medmnist-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3440
- Accuracy: 0.8622
- Precision: 0.8623
- Recall: 0.8402
- F1: 0.8487

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6158        | 0.9898 | 73   | 0.5674          | 0.7424   | 0.3712    | 0.5    | 0.4261 |
| 0.5322        | 1.9932 | 147  | 0.4840          | 0.7729   | 0.8829    | 0.5593 | 0.5396 |
| 0.4139        | 2.9966 | 221  | 0.3727          | 0.7939   | 0.8913    | 0.6    | 0.6057 |
| 0.3979        | 4.0    | 295  | 0.5270          | 0.7309   | 0.7405    | 0.8139 | 0.7168 |
| 0.3858        | 4.9898 | 368  | 0.3062          | 0.8531   | 0.8073    | 0.8623 | 0.8253 |
| 0.3704        | 5.9932 | 442  | 0.3774          | 0.8263   | 0.7939    | 0.8734 | 0.8056 |
| 0.3345        | 6.9966 | 516  | 0.2403          | 0.9027   | 0.8691    | 0.8812 | 0.8749 |
| 0.3875        | 8.0    | 590  | 0.3021          | 0.8817   | 0.8389    | 0.8985 | 0.8590 |
| 0.3673        | 8.9898 | 663  | 0.2865          | 0.8969   | 0.8557    | 0.9064 | 0.8749 |
| 0.3493        | 9.8983 | 730  | 0.3024          | 0.8740   | 0.8314    | 0.8958 | 0.8515 |


### Framework versions

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