transformers tensorboard safetensors 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_5x_deit_base_sgd_001_fold2
  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: 0.4888888888888889
---

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# hushem_5x_deit_base_sgd_001_fold2

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: 1.2313
- Accuracy: 0.4889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4159        | 1.0   | 27   | 1.4534          | 0.1333   |
| 1.3715        | 2.0   | 54   | 1.4329          | 0.1333   |
| 1.349         | 3.0   | 81   | 1.4161          | 0.1556   |
| 1.3491        | 4.0   | 108  | 1.4025          | 0.1556   |
| 1.3037        | 5.0   | 135  | 1.3915          | 0.2      |
| 1.2977        | 6.0   | 162  | 1.3813          | 0.2444   |
| 1.2881        | 7.0   | 189  | 1.3728          | 0.2889   |
| 1.2735        | 8.0   | 216  | 1.3643          | 0.3333   |
| 1.2461        | 9.0   | 243  | 1.3568          | 0.3556   |
| 1.2282        | 10.0  | 270  | 1.3495          | 0.3556   |
| 1.2197        | 11.0  | 297  | 1.3426          | 0.3556   |
| 1.1815        | 12.0  | 324  | 1.3361          | 0.3778   |
| 1.1874        | 13.0  | 351  | 1.3296          | 0.3778   |
| 1.1512        | 14.0  | 378  | 1.3234          | 0.3778   |
| 1.169         | 15.0  | 405  | 1.3177          | 0.4      |
| 1.1635        | 16.0  | 432  | 1.3122          | 0.4      |
| 1.1212        | 17.0  | 459  | 1.3068          | 0.4      |
| 1.1132        | 18.0  | 486  | 1.3013          | 0.4      |
| 1.0934        | 19.0  | 513  | 1.2960          | 0.4      |
| 1.0783        | 20.0  | 540  | 1.2914          | 0.4      |
| 1.0674        | 21.0  | 567  | 1.2869          | 0.4      |
| 1.0564        | 22.0  | 594  | 1.2826          | 0.4222   |
| 1.0602        | 23.0  | 621  | 1.2784          | 0.4444   |
| 1.0292        | 24.0  | 648  | 1.2744          | 0.4667   |
| 1.0348        | 25.0  | 675  | 1.2706          | 0.4667   |
| 1.0373        | 26.0  | 702  | 1.2671          | 0.4667   |
| 1.0143        | 27.0  | 729  | 1.2638          | 0.4667   |
| 1.0044        | 28.0  | 756  | 1.2607          | 0.4667   |
| 0.9861        | 29.0  | 783  | 1.2578          | 0.4667   |
| 1.0112        | 30.0  | 810  | 1.2551          | 0.4667   |
| 0.9561        | 31.0  | 837  | 1.2525          | 0.4667   |
| 0.9839        | 32.0  | 864  | 1.2500          | 0.4667   |
| 0.9768        | 33.0  | 891  | 1.2477          | 0.4667   |
| 0.936         | 34.0  | 918  | 1.2456          | 0.4667   |
| 0.9571        | 35.0  | 945  | 1.2436          | 0.4667   |
| 0.9423        | 36.0  | 972  | 1.2418          | 0.4667   |
| 0.9413        | 37.0  | 999  | 1.2401          | 0.4667   |
| 0.9304        | 38.0  | 1026 | 1.2386          | 0.4889   |
| 0.9391        | 39.0  | 1053 | 1.2372          | 0.4889   |
| 0.9013        | 40.0  | 1080 | 1.2360          | 0.4889   |
| 0.9198        | 41.0  | 1107 | 1.2349          | 0.4889   |
| 0.9119        | 42.0  | 1134 | 1.2340          | 0.4889   |
| 0.9214        | 43.0  | 1161 | 1.2332          | 0.4889   |
| 0.8928        | 44.0  | 1188 | 1.2325          | 0.4889   |
| 0.9196        | 45.0  | 1215 | 1.2320          | 0.4889   |
| 0.906         | 46.0  | 1242 | 1.2316          | 0.4889   |
| 0.9098        | 47.0  | 1269 | 1.2314          | 0.4889   |
| 0.9113        | 48.0  | 1296 | 1.2313          | 0.4889   |
| 0.9534        | 49.0  | 1323 | 1.2313          | 0.4889   |
| 0.8999        | 50.0  | 1350 | 1.2313          | 0.4889   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
