---
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: breastmnist-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. -->

# breastmnist-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: 0.3832
- Accuracy: 0.8333
- Precision: 0.8079
- Recall: 0.7431
- F1: 0.7653

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.9143 | 8    | 0.5026          | 0.7436   | 0.8701    | 0.5238 | 0.4708 |
| 0.6168        | 1.9429 | 17   | 0.4762          | 0.8462   | 0.8286    | 0.7594 | 0.7833 |
| 0.5954        | 2.9714 | 26   | 0.5305          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.5934        | 4.0    | 35   | 0.4790          | 0.7692   | 0.7836    | 0.5865 | 0.5846 |
| 0.526         | 4.9143 | 43   | 0.3693          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |
| 0.4651        | 5.9429 | 52   | 0.4789          | 0.7949   | 0.7434    | 0.7694 | 0.7534 |
| 0.493         | 6.9714 | 61   | 0.4187          | 0.8205   | 0.7792    | 0.7419 | 0.7565 |
| 0.4337        | 8.0    | 70   | 0.3600          | 0.8590   | 0.8417    | 0.7832 | 0.8051 |
| 0.4337        | 8.9143 | 78   | 0.3468          | 0.8718   | 0.8544    | 0.8070 | 0.8260 |
| 0.418         | 9.1429 | 80   | 0.3454          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |


### Framework versions

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