---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- medmnist-v2
metrics:
- accuracy
- f1
model-index:
- name: ViT_breastmnist_std_0
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: medmnist-v2
      type: medmnist-v2
      config: breastmnist
      split: validation
      args: breastmnist
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8717948717948718
    - name: F1
      type: f1
      value: 0.8370927318295739
---

<!-- 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. -->

# ViT_breastmnist_std_0

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the medmnist-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3272
- Accuracy: 0.8718
- F1: 0.8371

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.3533        | 0.2597 | 20   | 0.3035          | 0.8846   | 0.8406 |
| 0.1354        | 0.5195 | 40   | 0.2280          | 0.8974   | 0.8655 |
| 0.0247        | 0.7792 | 60   | 0.2669          | 0.9231   | 0.8956 |
| 0.0089        | 1.0390 | 80   | 0.2742          | 0.9231   | 0.8956 |
| 0.003         | 1.2987 | 100  | 0.3404          | 0.9103   | 0.8803 |
| 0.0018        | 1.5584 | 120  | 0.3583          | 0.9231   | 0.8956 |
| 0.0013        | 1.8182 | 140  | 0.3720          | 0.9231   | 0.8956 |
| 0.0009        | 2.0779 | 160  | 0.3892          | 0.9231   | 0.8956 |
| 0.0007        | 2.3377 | 180  | 0.3933          | 0.9231   | 0.8956 |
| 0.0006        | 2.5974 | 200  | 0.3948          | 0.9231   | 0.8956 |
| 0.0005        | 2.8571 | 220  | 0.4038          | 0.9231   | 0.8956 |
| 0.0005        | 3.1169 | 240  | 0.4145          | 0.9231   | 0.8956 |
| 0.0004        | 3.3766 | 260  | 0.4176          | 0.9231   | 0.8956 |
| 0.0004        | 3.6364 | 280  | 0.4230          | 0.9231   | 0.8956 |
| 0.0003        | 3.8961 | 300  | 0.4274          | 0.9103   | 0.8803 |
| 0.0003        | 4.1558 | 320  | 0.4344          | 0.9231   | 0.8956 |
| 0.0003        | 4.4156 | 340  | 0.4380          | 0.9231   | 0.8956 |
| 0.0003        | 4.6753 | 360  | 0.4406          | 0.9103   | 0.8803 |
| 0.0003        | 4.9351 | 380  | 0.4459          | 0.9231   | 0.8956 |
| 0.0002        | 5.1948 | 400  | 0.4472          | 0.9103   | 0.8803 |
| 0.0002        | 5.4545 | 420  | 0.4514          | 0.9103   | 0.8803 |
| 0.0002        | 5.7143 | 440  | 0.4550          | 0.9231   | 0.8956 |
| 0.0002        | 5.9740 | 460  | 0.4579          | 0.9231   | 0.8956 |
| 0.0002        | 6.2338 | 480  | 0.4600          | 0.9231   | 0.8956 |
| 0.0002        | 6.4935 | 500  | 0.4614          | 0.9103   | 0.8803 |
| 0.0002        | 6.7532 | 520  | 0.4637          | 0.9231   | 0.8956 |
| 0.0002        | 7.0130 | 540  | 0.4660          | 0.9231   | 0.8956 |
| 0.0002        | 7.2727 | 560  | 0.4684          | 0.9231   | 0.8956 |
| 0.0002        | 7.5325 | 580  | 0.4695          | 0.9231   | 0.8956 |
| 0.0002        | 7.7922 | 600  | 0.4710          | 0.9103   | 0.8803 |
| 0.0001        | 8.0519 | 620  | 0.4719          | 0.9103   | 0.8803 |
| 0.0001        | 8.3117 | 640  | 0.4726          | 0.9103   | 0.8803 |
| 0.0001        | 8.5714 | 660  | 0.4742          | 0.9103   | 0.8803 |
| 0.0001        | 8.8312 | 680  | 0.4754          | 0.9231   | 0.8956 |
| 0.0002        | 9.0909 | 700  | 0.4757          | 0.9231   | 0.8956 |
| 0.0001        | 9.3506 | 720  | 0.4759          | 0.9231   | 0.8956 |
| 0.0001        | 9.6104 | 740  | 0.4763          | 0.9231   | 0.8956 |
| 0.0001        | 9.8701 | 760  | 0.4765          | 0.9231   | 0.8956 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0