---
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_60
  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: 0.7756410256410257
    - name: F1
      type: f1
      value: 0.6137247966041741
---

<!-- 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_60

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: 0.5157
- Accuracy: 0.7756
- F1: 0.6137

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5179        | 0.2597 | 20   | 0.5240          | 0.7436   | 0.5385 |
| 0.4306        | 0.5195 | 40   | 0.4807          | 0.7949   | 0.6855 |
| 0.4258        | 0.7792 | 60   | 0.4812          | 0.7949   | 0.6518 |
| 0.4613        | 1.0390 | 80   | 0.4491          | 0.8333   | 0.7247 |
| 0.4194        | 1.2987 | 100  | 0.4573          | 0.8333   | 0.7247 |
| 0.3693        | 1.5584 | 120  | 0.4665          | 0.8205   | 0.6953 |
| 0.3825        | 1.8182 | 140  | 0.4695          | 0.7821   | 0.6733 |
| 0.387         | 2.0779 | 160  | 0.4410          | 0.8205   | 0.7248 |
| 0.3341        | 2.3377 | 180  | 0.4422          | 0.8205   | 0.7367 |
| 0.3192        | 2.5974 | 200  | 0.4457          | 0.8205   | 0.7111 |
| 0.3062        | 2.8571 | 220  | 0.4575          | 0.8205   | 0.7111 |
| 0.2485        | 3.1169 | 240  | 0.4526          | 0.8333   | 0.7383 |
| 0.2415        | 3.3766 | 260  | 0.4430          | 0.8462   | 0.7641 |
| 0.2377        | 3.6364 | 280  | 0.4529          | 0.8333   | 0.7247 |
| 0.2417        | 3.8961 | 300  | 0.4386          | 0.8205   | 0.7111 |
| 0.1783        | 4.1558 | 320  | 0.4467          | 0.8333   | 0.7383 |
| 0.193         | 4.4156 | 340  | 0.4724          | 0.8077   | 0.6823 |
| 0.1736        | 4.6753 | 360  | 0.4757          | 0.8333   | 0.7383 |
| 0.1656        | 4.9351 | 380  | 0.4677          | 0.8333   | 0.7383 |
| 0.1214        | 5.1948 | 400  | 0.4747          | 0.8077   | 0.6981 |
| 0.0851        | 5.4545 | 420  | 0.4782          | 0.7949   | 0.6698 |
| 0.0893        | 5.7143 | 440  | 0.4842          | 0.8077   | 0.6823 |
| 0.0978        | 5.9740 | 460  | 0.4883          | 0.8077   | 0.6823 |
| 0.0518        | 6.2338 | 480  | 0.4861          | 0.8077   | 0.6981 |
| 0.0662        | 6.4935 | 500  | 0.5017          | 0.8077   | 0.6981 |
| 0.058         | 6.7532 | 520  | 0.5092          | 0.7949   | 0.6518 |
| 0.0511        | 7.0130 | 540  | 0.5003          | 0.8205   | 0.7111 |
| 0.0235        | 7.2727 | 560  | 0.5041          | 0.8077   | 0.6823 |
| 0.0204        | 7.5325 | 580  | 0.5140          | 0.8205   | 0.7111 |
| 0.0196        | 7.7922 | 600  | 0.5122          | 0.8205   | 0.7111 |
| 0.0108        | 8.0519 | 620  | 0.5186          | 0.8205   | 0.7111 |
| 0.012         | 8.3117 | 640  | 0.5315          | 0.8333   | 0.7247 |
| 0.0077        | 8.5714 | 660  | 0.5319          | 0.8205   | 0.7111 |
| 0.0187        | 8.8312 | 680  | 0.5279          | 0.8205   | 0.7111 |
| 0.0063        | 9.0909 | 700  | 0.5304          | 0.8205   | 0.7111 |
| 0.004         | 9.3506 | 720  | 0.5312          | 0.8205   | 0.7111 |
| 0.0044        | 9.6104 | 740  | 0.5310          | 0.8205   | 0.7111 |
| 0.0076        | 9.8701 | 760  | 0.5323          | 0.8205   | 0.7111 |


### Framework versions

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