transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_adamax_00001_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: 0.6666666666666666
---

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# hushem_1x_deit_tiny_adamax_00001_fold4

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8218
- Accuracy: 0.6667

## 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: 1e-05
- 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    | 1.3850          | 0.3333   |
| 1.4335        | 2.0   | 12   | 1.3341          | 0.3571   |
| 1.4335        | 3.0   | 18   | 1.2836          | 0.4286   |
| 1.2369        | 4.0   | 24   | 1.2256          | 0.5238   |
| 1.1106        | 5.0   | 30   | 1.1743          | 0.4762   |
| 1.1106        | 6.0   | 36   | 1.1379          | 0.5238   |
| 0.9897        | 7.0   | 42   | 1.1120          | 0.5952   |
| 0.9897        | 8.0   | 48   | 1.0871          | 0.6190   |
| 0.869         | 9.0   | 54   | 1.0617          | 0.5952   |
| 0.7919        | 10.0  | 60   | 1.0389          | 0.5952   |
| 0.7919        | 11.0  | 66   | 1.0206          | 0.5714   |
| 0.7005        | 12.0  | 72   | 1.0005          | 0.5714   |
| 0.7005        | 13.0  | 78   | 0.9876          | 0.5714   |
| 0.6273        | 14.0  | 84   | 0.9709          | 0.5952   |
| 0.5477        | 15.0  | 90   | 0.9546          | 0.5952   |
| 0.5477        | 16.0  | 96   | 0.9438          | 0.5714   |
| 0.4708        | 17.0  | 102  | 0.9277          | 0.5952   |
| 0.4708        | 18.0  | 108  | 0.9166          | 0.6190   |
| 0.4523        | 19.0  | 114  | 0.9086          | 0.6190   |
| 0.3797        | 20.0  | 120  | 0.9051          | 0.5952   |
| 0.3797        | 21.0  | 126  | 0.8956          | 0.6190   |
| 0.3458        | 22.0  | 132  | 0.8852          | 0.6190   |
| 0.3458        | 23.0  | 138  | 0.8841          | 0.6190   |
| 0.3057        | 24.0  | 144  | 0.8804          | 0.5952   |
| 0.2867        | 25.0  | 150  | 0.8683          | 0.6429   |
| 0.2867        | 26.0  | 156  | 0.8580          | 0.6667   |
| 0.2509        | 27.0  | 162  | 0.8515          | 0.6667   |
| 0.2509        | 28.0  | 168  | 0.8546          | 0.6429   |
| 0.2322        | 29.0  | 174  | 0.8500          | 0.6667   |
| 0.2064        | 30.0  | 180  | 0.8396          | 0.6667   |
| 0.2064        | 31.0  | 186  | 0.8363          | 0.6667   |
| 0.1928        | 32.0  | 192  | 0.8371          | 0.6667   |
| 0.1928        | 33.0  | 198  | 0.8332          | 0.6667   |
| 0.1767        | 34.0  | 204  | 0.8261          | 0.6667   |
| 0.1746        | 35.0  | 210  | 0.8249          | 0.6667   |
| 0.1746        | 36.0  | 216  | 0.8258          | 0.6667   |
| 0.1557        | 37.0  | 222  | 0.8248          | 0.6667   |
| 0.1557        | 38.0  | 228  | 0.8243          | 0.6667   |
| 0.1581        | 39.0  | 234  | 0.8225          | 0.6667   |
| 0.1477        | 40.0  | 240  | 0.8219          | 0.6667   |
| 0.1477        | 41.0  | 246  | 0.8217          | 0.6667   |
| 0.149         | 42.0  | 252  | 0.8218          | 0.6667   |
| 0.149         | 43.0  | 258  | 0.8218          | 0.6667   |
| 0.1403        | 44.0  | 264  | 0.8218          | 0.6667   |
| 0.146         | 45.0  | 270  | 0.8218          | 0.6667   |
| 0.146         | 46.0  | 276  | 0.8218          | 0.6667   |
| 0.1461        | 47.0  | 282  | 0.8218          | 0.6667   |
| 0.1461        | 48.0  | 288  | 0.8218          | 0.6667   |
| 0.1422        | 49.0  | 294  | 0.8218          | 0.6667   |
| 0.1494        | 50.0  | 300  | 0.8218          | 0.6667   |


### Framework versions

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