---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: rsna-intracranial-hemorrhage-detection
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6151724137931035
---

<!-- 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. -->

# rsna-intracranial-hemorrhage-detection

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2164
- Accuracy: 0.6152

## 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: 5e-05
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5655        | 1.0   | 238   | 1.5235          | 0.4039   |
| 1.3848        | 2.0   | 477   | 1.3622          | 0.4692   |
| 1.2812        | 3.0   | 716   | 1.2811          | 0.5150   |
| 1.2039        | 4.0   | 955   | 1.1795          | 0.5556   |
| 1.1641        | 5.0   | 1193  | 1.1627          | 0.5534   |
| 1.1961        | 6.0   | 1432  | 1.1393          | 0.5705   |
| 1.1382        | 7.0   | 1671  | 1.0921          | 0.5804   |
| 0.9653        | 8.0   | 1910  | 1.0790          | 0.5876   |
| 0.9346        | 9.0   | 2148  | 1.0727          | 0.5931   |
| 0.9083        | 10.0  | 2387  | 1.0605          | 0.5994   |
| 0.8936        | 11.0  | 2626  | 1.0147          | 0.6146   |
| 0.8504        | 12.0  | 2865  | 1.0849          | 0.5818   |
| 0.8544        | 13.0  | 3103  | 1.0349          | 0.6052   |
| 0.7884        | 14.0  | 3342  | 1.0435          | 0.6074   |
| 0.7974        | 15.0  | 3581  | 1.0082          | 0.6127   |
| 0.7921        | 16.0  | 3820  | 1.0438          | 0.6017   |
| 0.709         | 17.0  | 4058  | 1.0484          | 0.6094   |
| 0.6646        | 18.0  | 4297  | 1.0554          | 0.6221   |
| 0.6832        | 19.0  | 4536  | 1.0455          | 0.6124   |
| 0.7076        | 20.0  | 4775  | 1.0905          | 0.6      |
| 0.7442        | 21.0  | 5013  | 1.1094          | 0.6008   |
| 0.6332        | 22.0  | 5252  | 1.0777          | 0.6063   |
| 0.6417        | 23.0  | 5491  | 1.0765          | 0.6141   |
| 0.6267        | 24.0  | 5730  | 1.1057          | 0.6091   |
| 0.6082        | 25.0  | 5968  | 1.0962          | 0.6171   |
| 0.6191        | 26.0  | 6207  | 1.1178          | 0.6039   |
| 0.5654        | 27.0  | 6446  | 1.1386          | 0.5948   |
| 0.5776        | 28.0  | 6685  | 1.1121          | 0.6105   |
| 0.5531        | 29.0  | 6923  | 1.1497          | 0.6030   |
| 0.6275        | 30.0  | 7162  | 1.1796          | 0.6028   |
| 0.5373        | 31.0  | 7401  | 1.1306          | 0.6132   |
| 0.4775        | 32.0  | 7640  | 1.1523          | 0.6058   |
| 0.5469        | 33.0  | 7878  | 1.1634          | 0.6127   |
| 0.4934        | 34.0  | 8117  | 1.1853          | 0.616    |
| 0.5233        | 35.0  | 8356  | 1.2018          | 0.6055   |
| 0.4896        | 36.0  | 8595  | 1.1585          | 0.6108   |
| 0.5122        | 37.0  | 8833  | 1.1874          | 0.6146   |
| 0.4726        | 38.0  | 9072  | 1.1608          | 0.6193   |
| 0.4372        | 39.0  | 9311  | 1.2403          | 0.6132   |
| 0.498         | 40.0  | 9550  | 1.1752          | 0.6201   |
| 0.4813        | 41.0  | 9788  | 1.2005          | 0.6166   |
| 0.4762        | 42.0  | 10027 | 1.2285          | 0.6022   |
| 0.4852        | 43.0  | 10266 | 1.2192          | 0.6119   |
| 0.4332        | 44.0  | 10505 | 1.2391          | 0.6218   |
| 0.3998        | 45.0  | 10743 | 1.1779          | 0.6196   |
| 0.4467        | 46.0  | 10982 | 1.2048          | 0.6284   |
| 0.4332        | 47.0  | 11221 | 1.2302          | 0.6188   |
| 0.4529        | 48.0  | 11460 | 1.2220          | 0.6188   |
| 0.4281        | 49.0  | 11698 | 1.2013          | 0.624    |
| 0.4199        | 49.84 | 11900 | 1.2164          | 0.6152   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3