transformers pytorch vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_rms_001_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: 0.5333333333333333
---

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# hushem_40x_deit_base_rms_001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 7.0637
- Accuracy: 0.5333

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3874        | 1.0   | 215   | 1.5845          | 0.2667   |
| 1.2829        | 2.0   | 430   | 1.2221          | 0.4      |
| 0.7962        | 3.0   | 645   | 2.1065          | 0.4      |
| 0.7528        | 4.0   | 860   | 1.0651          | 0.5556   |
| 0.6029        | 5.0   | 1075  | 1.5642          | 0.4889   |
| 0.6246        | 6.0   | 1290  | 1.7962          | 0.4222   |
| 0.589         | 7.0   | 1505  | 1.4819          | 0.4444   |
| 0.6081        | 8.0   | 1720  | 1.4452          | 0.4222   |
| 0.4808        | 9.0   | 1935  | 1.4389          | 0.4444   |
| 0.4155        | 10.0  | 2150  | 1.7698          | 0.4667   |
| 0.4393        | 11.0  | 2365  | 1.4569          | 0.5778   |
| 0.4007        | 12.0  | 2580  | 2.1115          | 0.4      |
| 0.3758        | 13.0  | 2795  | 1.5230          | 0.5556   |
| 0.3244        | 14.0  | 3010  | 2.2901          | 0.4444   |
| 0.3063        | 15.0  | 3225  | 2.0129          | 0.4889   |
| 0.3072        | 16.0  | 3440  | 2.2969          | 0.5333   |
| 0.2444        | 17.0  | 3655  | 2.5054          | 0.4667   |
| 0.2293        | 18.0  | 3870  | 2.3449          | 0.4889   |
| 0.2391        | 19.0  | 4085  | 2.0401          | 0.6444   |
| 0.1843        | 20.0  | 4300  | 2.7271          | 0.5333   |
| 0.2073        | 21.0  | 4515  | 2.2599          | 0.4889   |
| 0.194         | 22.0  | 4730  | 3.1378          | 0.4444   |
| 0.2943        | 23.0  | 4945  | 2.7236          | 0.5333   |
| 0.2089        | 24.0  | 5160  | 2.5054          | 0.5778   |
| 0.2145        | 25.0  | 5375  | 3.8073          | 0.4667   |
| 0.1232        | 26.0  | 5590  | 3.5697          | 0.4889   |
| 0.1349        | 27.0  | 5805  | 3.5985          | 0.5333   |
| 0.1548        | 28.0  | 6020  | 3.0930          | 0.4889   |
| 0.0655        | 29.0  | 6235  | 4.3232          | 0.4889   |
| 0.1304        | 30.0  | 6450  | 3.6994          | 0.5333   |
| 0.0997        | 31.0  | 6665  | 3.7329          | 0.5333   |
| 0.0825        | 32.0  | 6880  | 3.4793          | 0.5333   |
| 0.154         | 33.0  | 7095  | 5.2562          | 0.4667   |
| 0.1206        | 34.0  | 7310  | 4.5299          | 0.4889   |
| 0.1019        | 35.0  | 7525  | 3.6522          | 0.5111   |
| 0.019         | 36.0  | 7740  | 3.9235          | 0.5333   |
| 0.0485        | 37.0  | 7955  | 4.7342          | 0.5556   |
| 0.0155        | 38.0  | 8170  | 4.4779          | 0.5778   |
| 0.0142        | 39.0  | 8385  | 4.2139          | 0.5556   |
| 0.0256        | 40.0  | 8600  | 5.0724          | 0.5333   |
| 0.0211        | 41.0  | 8815  | 4.8895          | 0.4889   |
| 0.019         | 42.0  | 9030  | 4.8291          | 0.5556   |
| 0.0047        | 43.0  | 9245  | 5.9102          | 0.5333   |
| 0.0027        | 44.0  | 9460  | 5.9480          | 0.5556   |
| 0.0009        | 45.0  | 9675  | 6.2260          | 0.5333   |
| 0.0008        | 46.0  | 9890  | 6.6029          | 0.5556   |
| 0.0001        | 47.0  | 10105 | 6.7925          | 0.5556   |
| 0.0001        | 48.0  | 10320 | 6.7039          | 0.5333   |
| 0.0           | 49.0  | 10535 | 7.0556          | 0.5333   |
| 0.0001        | 50.0  | 10750 | 7.0637          | 0.5333   |


### Framework versions

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