---
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: breastmnist-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. -->

# breastmnist-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: 0.5228
- Accuracy: 0.7308
- Precision: 0.3654
- Recall: 0.5
- F1: 0.4222

## 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    | 0.8325          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.7315        | 1.9429 | 17   | 0.5744          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.6223        | 2.9714 | 26   | 0.5911          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.5815        | 4.0    | 35   | 0.5743          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.5627        | 4.9143 | 43   | 0.6546          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.5552        | 5.9429 | 52   | 0.5381          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.536         | 6.9714 | 61   | 0.5101          | 0.7949   | 0.8904    | 0.6190 | 0.6308 |
| 0.5454        | 8.0    | 70   | 0.5273          | 0.7692   | 0.7246    | 0.6165 | 0.6286 |
| 0.5454        | 8.9143 | 78   | 0.5176          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
| 0.5058        | 9.1429 | 80   | 0.5228          | 0.7308   | 0.3654    | 0.5    | 0.4222 |


### Framework versions

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