transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_adamax_001_fold4
  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: 0.5952380952380952
---

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# hushem_1x_deit_small_adamax_001_fold4

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1234
- Accuracy: 0.5952

## 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    | 1.5633          | 0.2381   |
| 1.7898        | 2.0   | 12   | 1.3816          | 0.2381   |
| 1.7898        | 3.0   | 18   | 1.3607          | 0.2619   |
| 1.4334        | 4.0   | 24   | 1.3501          | 0.2619   |
| 1.3732        | 5.0   | 30   | 1.3553          | 0.2381   |
| 1.3732        | 6.0   | 36   | 1.1841          | 0.4762   |
| 1.3036        | 7.0   | 42   | 1.0576          | 0.5952   |
| 1.3036        | 8.0   | 48   | 1.0689          | 0.5952   |
| 1.2142        | 9.0   | 54   | 1.2296          | 0.5      |
| 1.056         | 10.0  | 60   | 0.7879          | 0.6429   |
| 1.056         | 11.0  | 66   | 0.7199          | 0.7143   |
| 0.921         | 12.0  | 72   | 0.9775          | 0.6190   |
| 0.921         | 13.0  | 78   | 0.8809          | 0.5952   |
| 0.6456        | 14.0  | 84   | 1.0792          | 0.5476   |
| 0.6348        | 15.0  | 90   | 1.0335          | 0.6190   |
| 0.6348        | 16.0  | 96   | 1.7853          | 0.5714   |
| 0.4743        | 17.0  | 102  | 1.5872          | 0.5714   |
| 0.4743        | 18.0  | 108  | 2.0651          | 0.5      |
| 0.2408        | 19.0  | 114  | 2.8369          | 0.4762   |
| 0.2271        | 20.0  | 120  | 2.1149          | 0.6190   |
| 0.2271        | 21.0  | 126  | 1.5722          | 0.6190   |
| 0.3385        | 22.0  | 132  | 2.8555          | 0.5476   |
| 0.3385        | 23.0  | 138  | 2.2068          | 0.6667   |
| 0.0822        | 24.0  | 144  | 2.2969          | 0.6190   |
| 0.0932        | 25.0  | 150  | 1.8785          | 0.7143   |
| 0.0932        | 26.0  | 156  | 3.2275          | 0.5714   |
| 0.0807        | 27.0  | 162  | 2.8847          | 0.5952   |
| 0.0807        | 28.0  | 168  | 3.1184          | 0.5952   |
| 0.0424        | 29.0  | 174  | 2.4583          | 0.6190   |
| 0.0287        | 30.0  | 180  | 2.8305          | 0.5714   |
| 0.0287        | 31.0  | 186  | 3.5171          | 0.5476   |
| 0.0333        | 32.0  | 192  | 3.2119          | 0.5952   |
| 0.0333        | 33.0  | 198  | 2.9811          | 0.5952   |
| 0.0008        | 34.0  | 204  | 3.0451          | 0.5952   |
| 0.0004        | 35.0  | 210  | 3.0670          | 0.5952   |
| 0.0004        | 36.0  | 216  | 3.0857          | 0.5952   |
| 0.0003        | 37.0  | 222  | 3.1009          | 0.5952   |
| 0.0003        | 38.0  | 228  | 3.1113          | 0.5952   |
| 0.0003        | 39.0  | 234  | 3.1177          | 0.5952   |
| 0.0003        | 40.0  | 240  | 3.1213          | 0.5952   |
| 0.0003        | 41.0  | 246  | 3.1231          | 0.5952   |
| 0.0002        | 42.0  | 252  | 3.1234          | 0.5952   |
| 0.0002        | 43.0  | 258  | 3.1234          | 0.5952   |
| 0.0002        | 44.0  | 264  | 3.1234          | 0.5952   |
| 0.0002        | 45.0  | 270  | 3.1234          | 0.5952   |
| 0.0002        | 46.0  | 276  | 3.1234          | 0.5952   |
| 0.0002        | 47.0  | 282  | 3.1234          | 0.5952   |
| 0.0002        | 48.0  | 288  | 3.1234          | 0.5952   |
| 0.0002        | 49.0  | 294  | 3.1234          | 0.5952   |
| 0.0002        | 50.0  | 300  | 3.1234          | 0.5952   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
