transformers pytorch beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_0001_fold1
  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: 0.8888888888888888
---

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# hushem_40x_beit_large_adamax_0001_fold1

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6987
- Accuracy: 0.8889

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0285        | 1.0   | 215   | 0.5849          | 0.8      |
| 0.0006        | 2.0   | 430   | 0.7781          | 0.8222   |
| 0.0           | 3.0   | 645   | 0.5158          | 0.8      |
| 0.0           | 4.0   | 860   | 0.4099          | 0.8444   |
| 0.0           | 5.0   | 1075  | 0.4040          | 0.8889   |
| 0.0           | 6.0   | 1290  | 0.4087          | 0.8889   |
| 0.0029        | 7.0   | 1505  | 0.2585          | 0.8889   |
| 0.0159        | 8.0   | 1720  | 0.6738          | 0.9111   |
| 0.0           | 9.0   | 1935  | 0.7387          | 0.8889   |
| 0.0           | 10.0  | 2150  | 0.3266          | 0.9111   |
| 0.0001        | 11.0  | 2365  | 0.5064          | 0.8667   |
| 0.0           | 12.0  | 2580  | 0.3031          | 0.9111   |
| 0.0           | 13.0  | 2795  | 0.3143          | 0.9111   |
| 0.0           | 14.0  | 3010  | 0.3219          | 0.9111   |
| 0.0           | 15.0  | 3225  | 0.3481          | 0.9111   |
| 0.0           | 16.0  | 3440  | 0.3485          | 0.9111   |
| 0.0           | 17.0  | 3655  | 0.3724          | 0.9111   |
| 0.0           | 18.0  | 3870  | 0.3706          | 0.8889   |
| 0.0           | 19.0  | 4085  | 0.3603          | 0.9111   |
| 0.0           | 20.0  | 4300  | 0.3742          | 0.9111   |
| 0.0           | 21.0  | 4515  | 0.5745          | 0.8444   |
| 0.0           | 22.0  | 4730  | 0.4247          | 0.8444   |
| 0.0           | 23.0  | 4945  | 0.4328          | 0.8667   |
| 0.0           | 24.0  | 5160  | 0.3958          | 0.8889   |
| 0.0           | 25.0  | 5375  | 0.4106          | 0.9111   |
| 0.0           | 26.0  | 5590  | 0.4237          | 0.8667   |
| 0.0           | 27.0  | 5805  | 0.4907          | 0.8667   |
| 0.0           | 28.0  | 6020  | 0.5123          | 0.8667   |
| 0.0           | 29.0  | 6235  | 0.4509          | 0.8889   |
| 0.0           | 30.0  | 6450  | 0.5376          | 0.8889   |
| 0.0           | 31.0  | 6665  | 0.5524          | 0.8889   |
| 0.0           | 32.0  | 6880  | 0.6004          | 0.8889   |
| 0.0           | 33.0  | 7095  | 0.5947          | 0.8889   |
| 0.0           | 34.0  | 7310  | 0.6506          | 0.8889   |
| 0.0           | 35.0  | 7525  | 0.8615          | 0.8889   |
| 0.0           | 36.0  | 7740  | 0.6453          | 0.8889   |
| 0.0           | 37.0  | 7955  | 0.6879          | 0.8889   |
| 0.0           | 38.0  | 8170  | 0.6869          | 0.8889   |
| 0.0           | 39.0  | 8385  | 0.7122          | 0.8889   |
| 0.0           | 40.0  | 8600  | 0.7111          | 0.8889   |
| 0.0           | 41.0  | 8815  | 0.7028          | 0.8889   |
| 0.0           | 42.0  | 9030  | 0.7091          | 0.8889   |
| 0.0           | 43.0  | 9245  | 0.7217          | 0.8889   |
| 0.0           | 44.0  | 9460  | 0.7018          | 0.8889   |
| 0.0           | 45.0  | 9675  | 0.7281          | 0.8889   |
| 0.0           | 46.0  | 9890  | 0.7227          | 0.8889   |
| 0.0           | 47.0  | 10105 | 0.7233          | 0.8889   |
| 0.0           | 48.0  | 10320 | 0.7063          | 0.8889   |
| 0.0           | 49.0  | 10535 | 0.6973          | 0.8889   |
| 0.0           | 50.0  | 10750 | 0.6987          | 0.8889   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
