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_5x_deit_tiny_rms_0001_fold5
  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: 0.8780487804878049
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hushem_5x_deit_tiny_rms_0001_fold5

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: 0.8418
- Accuracy: 0.8780

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4959        | 1.0   | 28   | 1.3943          | 0.2439   |
| 1.4016        | 2.0   | 56   | 1.1344          | 0.4146   |
| 0.8658        | 3.0   | 84   | 0.7965          | 0.7073   |
| 0.4771        | 4.0   | 112  | 0.8323          | 0.7073   |
| 0.2251        | 5.0   | 140  | 0.3450          | 0.8537   |
| 0.161         | 6.0   | 168  | 1.1238          | 0.5854   |
| 0.122         | 7.0   | 196  | 0.5699          | 0.8780   |
| 0.0493        | 8.0   | 224  | 1.1342          | 0.6585   |
| 0.0526        | 9.0   | 252  | 1.0124          | 0.8293   |
| 0.0543        | 10.0  | 280  | 1.4922          | 0.8537   |
| 0.0179        | 11.0  | 308  | 0.4348          | 0.9024   |
| 0.001         | 12.0  | 336  | 0.7229          | 0.8293   |
| 0.0002        | 13.0  | 364  | 0.6260          | 0.8780   |
| 0.0001        | 14.0  | 392  | 0.6381          | 0.8780   |
| 0.0001        | 15.0  | 420  | 0.6479          | 0.8780   |
| 0.0001        | 16.0  | 448  | 0.6572          | 0.8780   |
| 0.0001        | 17.0  | 476  | 0.6669          | 0.8780   |
| 0.0           | 18.0  | 504  | 0.6750          | 0.8780   |
| 0.0           | 19.0  | 532  | 0.6816          | 0.8780   |
| 0.0           | 20.0  | 560  | 0.6897          | 0.8780   |
| 0.0           | 21.0  | 588  | 0.6973          | 0.8780   |
| 0.0           | 22.0  | 616  | 0.7042          | 0.8780   |
| 0.0           | 23.0  | 644  | 0.7114          | 0.8780   |
| 0.0           | 24.0  | 672  | 0.7182          | 0.8780   |
| 0.0           | 25.0  | 700  | 0.7246          | 0.8780   |
| 0.0           | 26.0  | 728  | 0.7318          | 0.8780   |
| 0.0           | 27.0  | 756  | 0.7392          | 0.8780   |
| 0.0           | 28.0  | 784  | 0.7454          | 0.8780   |
| 0.0           | 29.0  | 812  | 0.7524          | 0.8780   |
| 0.0           | 30.0  | 840  | 0.7588          | 0.8780   |
| 0.0           | 31.0  | 868  | 0.7650          | 0.8780   |
| 0.0           | 32.0  | 896  | 0.7711          | 0.8780   |
| 0.0           | 33.0  | 924  | 0.7761          | 0.8780   |
| 0.0           | 34.0  | 952  | 0.7832          | 0.8780   |
| 0.0           | 35.0  | 980  | 0.7888          | 0.8780   |
| 0.0           | 36.0  | 1008 | 0.7948          | 0.8780   |
| 0.0           | 37.0  | 1036 | 0.8020          | 0.8780   |
| 0.0           | 38.0  | 1064 | 0.8075          | 0.8780   |
| 0.0           | 39.0  | 1092 | 0.8124          | 0.8780   |
| 0.0           | 40.0  | 1120 | 0.8170          | 0.8780   |
| 0.0           | 41.0  | 1148 | 0.8223          | 0.8780   |
| 0.0           | 42.0  | 1176 | 0.8266          | 0.8780   |
| 0.0           | 43.0  | 1204 | 0.8300          | 0.8780   |
| 0.0           | 44.0  | 1232 | 0.8327          | 0.8780   |
| 0.0           | 45.0  | 1260 | 0.8359          | 0.8780   |
| 0.0           | 46.0  | 1288 | 0.8390          | 0.8780   |
| 0.0           | 47.0  | 1316 | 0.8409          | 0.8780   |
| 0.0           | 48.0  | 1344 | 0.8418          | 0.8780   |
| 0.0           | 49.0  | 1372 | 0.8418          | 0.8780   |
| 0.0           | 50.0  | 1400 | 0.8418          | 0.8780   |


### Framework versions

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