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_1x_deit_base_sgd_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: 0.2222222222222222
---

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# hushem_1x_deit_base_sgd_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: 1.4169
- Accuracy: 0.2222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5144          | 0.1333   |
| 1.4099        | 2.0   | 12   | 1.5058          | 0.1333   |
| 1.4099        | 3.0   | 18   | 1.4975          | 0.1333   |
| 1.3953        | 4.0   | 24   | 1.4914          | 0.1333   |
| 1.3839        | 5.0   | 30   | 1.4843          | 0.1556   |
| 1.3839        | 6.0   | 36   | 1.4779          | 0.1778   |
| 1.3707        | 7.0   | 42   | 1.4724          | 0.1778   |
| 1.3707        | 8.0   | 48   | 1.4679          | 0.1778   |
| 1.3722        | 9.0   | 54   | 1.4633          | 0.1778   |
| 1.3434        | 10.0  | 60   | 1.4589          | 0.1778   |
| 1.3434        | 11.0  | 66   | 1.4552          | 0.2      |
| 1.3467        | 12.0  | 72   | 1.4521          | 0.2      |
| 1.3467        | 13.0  | 78   | 1.4488          | 0.2      |
| 1.3313        | 14.0  | 84   | 1.4460          | 0.2      |
| 1.33          | 15.0  | 90   | 1.4434          | 0.2      |
| 1.33          | 16.0  | 96   | 1.4413          | 0.2      |
| 1.325         | 17.0  | 102  | 1.4392          | 0.2      |
| 1.325         | 18.0  | 108  | 1.4371          | 0.2      |
| 1.3231        | 19.0  | 114  | 1.4349          | 0.2222   |
| 1.3131        | 20.0  | 120  | 1.4330          | 0.2222   |
| 1.3131        | 21.0  | 126  | 1.4314          | 0.2444   |
| 1.3095        | 22.0  | 132  | 1.4300          | 0.2444   |
| 1.3095        | 23.0  | 138  | 1.4284          | 0.2444   |
| 1.3181        | 24.0  | 144  | 1.4271          | 0.2444   |
| 1.2959        | 25.0  | 150  | 1.4260          | 0.2222   |
| 1.2959        | 26.0  | 156  | 1.4247          | 0.2222   |
| 1.2924        | 27.0  | 162  | 1.4239          | 0.2222   |
| 1.2924        | 28.0  | 168  | 1.4230          | 0.2222   |
| 1.2867        | 29.0  | 174  | 1.4221          | 0.2222   |
| 1.2887        | 30.0  | 180  | 1.4212          | 0.2222   |
| 1.2887        | 31.0  | 186  | 1.4204          | 0.2222   |
| 1.2851        | 32.0  | 192  | 1.4198          | 0.2222   |
| 1.2851        | 33.0  | 198  | 1.4193          | 0.2222   |
| 1.2896        | 34.0  | 204  | 1.4187          | 0.2222   |
| 1.2742        | 35.0  | 210  | 1.4183          | 0.2222   |
| 1.2742        | 36.0  | 216  | 1.4179          | 0.2222   |
| 1.2726        | 37.0  | 222  | 1.4176          | 0.2222   |
| 1.2726        | 38.0  | 228  | 1.4173          | 0.2222   |
| 1.2881        | 39.0  | 234  | 1.4171          | 0.2222   |
| 1.2721        | 40.0  | 240  | 1.4170          | 0.2222   |
| 1.2721        | 41.0  | 246  | 1.4169          | 0.2222   |
| 1.2788        | 42.0  | 252  | 1.4169          | 0.2222   |
| 1.2788        | 43.0  | 258  | 1.4169          | 0.2222   |
| 1.2737        | 44.0  | 264  | 1.4169          | 0.2222   |
| 1.2763        | 45.0  | 270  | 1.4169          | 0.2222   |
| 1.2763        | 46.0  | 276  | 1.4169          | 0.2222   |
| 1.2804        | 47.0  | 282  | 1.4169          | 0.2222   |
| 1.2804        | 48.0  | 288  | 1.4169          | 0.2222   |
| 1.2603        | 49.0  | 294  | 1.4169          | 0.2222   |
| 1.275         | 50.0  | 300  | 1.4169          | 0.2222   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0
