---
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: organamnist-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. -->

# organamnist-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: 0.1907
- Accuracy: 0.9424
- Precision: 0.9464
- Recall: 0.9395
- F1: 0.9421

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5849        | 1.0   | 540  | 0.1842          | 0.9442   | 0.9449    | 0.9268 | 0.9285 |
| 0.6494        | 2.0   | 1081 | 0.1433          | 0.9499   | 0.9539    | 0.9510 | 0.9509 |
| 0.6059        | 3.0   | 1621 | 0.1171          | 0.9562   | 0.9659    | 0.9569 | 0.9593 |
| 0.3547        | 4.0   | 2162 | 0.0981          | 0.9666   | 0.9709    | 0.9712 | 0.9702 |
| 0.4852        | 5.0   | 2702 | 0.0539          | 0.9817   | 0.9848    | 0.9842 | 0.9842 |
| 0.406         | 6.0   | 3243 | 0.0818          | 0.9749   | 0.9793    | 0.9752 | 0.9768 |
| 0.3074        | 7.0   | 3783 | 0.1289          | 0.9666   | 0.9815    | 0.9778 | 0.9783 |
| 0.2679        | 8.0   | 4324 | 0.0311          | 0.9900   | 0.9916    | 0.9909 | 0.9912 |
| 0.2439        | 9.0   | 4864 | 0.0577          | 0.9851   | 0.9886    | 0.9880 | 0.9881 |
| 0.2169        | 9.99  | 5400 | 0.0720          | 0.9835   | 0.9888    | 0.9882 | 0.9882 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2