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_rms_001_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: 0.6097560975609756
---

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# hushem_1x_deit_tiny_rms_001_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: 1.1358
- Accuracy: 0.6098

## 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    | 4.7231          | 0.2683   |
| 4.2141        | 2.0   | 12   | 1.8531          | 0.2683   |
| 4.2141        | 3.0   | 18   | 1.6449          | 0.2439   |
| 1.9845        | 4.0   | 24   | 1.4265          | 0.2439   |
| 1.5807        | 5.0   | 30   | 2.0165          | 0.2439   |
| 1.5807        | 6.0   | 36   | 1.5975          | 0.2683   |
| 1.5979        | 7.0   | 42   | 1.4305          | 0.3171   |
| 1.5979        | 8.0   | 48   | 1.4587          | 0.2683   |
| 1.4992        | 9.0   | 54   | 1.2917          | 0.3171   |
| 1.4954        | 10.0  | 60   | 1.2462          | 0.4390   |
| 1.4954        | 11.0  | 66   | 1.2479          | 0.2683   |
| 1.415         | 12.0  | 72   | 1.1246          | 0.5122   |
| 1.415         | 13.0  | 78   | 1.1689          | 0.4878   |
| 1.374         | 14.0  | 84   | 1.3767          | 0.2927   |
| 1.3675        | 15.0  | 90   | 1.1692          | 0.4146   |
| 1.3675        | 16.0  | 96   | 1.6528          | 0.2927   |
| 1.319         | 17.0  | 102  | 1.3151          | 0.3659   |
| 1.319         | 18.0  | 108  | 1.1475          | 0.4146   |
| 1.3335        | 19.0  | 114  | 1.1506          | 0.3415   |
| 1.2819        | 20.0  | 120  | 1.2300          | 0.3902   |
| 1.2819        | 21.0  | 126  | 1.1641          | 0.4146   |
| 1.2507        | 22.0  | 132  | 1.4148          | 0.3659   |
| 1.2507        | 23.0  | 138  | 1.3061          | 0.3415   |
| 1.2134        | 24.0  | 144  | 1.2367          | 0.3415   |
| 1.2611        | 25.0  | 150  | 1.2383          | 0.4878   |
| 1.2611        | 26.0  | 156  | 1.0375          | 0.4878   |
| 1.2053        | 27.0  | 162  | 1.1983          | 0.4878   |
| 1.2053        | 28.0  | 168  | 1.1898          | 0.4146   |
| 1.1593        | 29.0  | 174  | 1.1479          | 0.4878   |
| 1.2426        | 30.0  | 180  | 1.1382          | 0.5610   |
| 1.2426        | 31.0  | 186  | 1.0558          | 0.5610   |
| 1.1866        | 32.0  | 192  | 1.1895          | 0.4390   |
| 1.1866        | 33.0  | 198  | 1.2172          | 0.4146   |
| 1.1453        | 34.0  | 204  | 1.3773          | 0.4146   |
| 1.1026        | 35.0  | 210  | 1.1168          | 0.5122   |
| 1.1026        | 36.0  | 216  | 1.1184          | 0.5610   |
| 1.131         | 37.0  | 222  | 1.1344          | 0.5366   |
| 1.131         | 38.0  | 228  | 1.0932          | 0.5122   |
| 1.1098        | 39.0  | 234  | 1.1070          | 0.6098   |
| 1.0797        | 40.0  | 240  | 1.1237          | 0.5854   |
| 1.0797        | 41.0  | 246  | 1.1366          | 0.6098   |
| 1.0648        | 42.0  | 252  | 1.1358          | 0.6098   |
| 1.0648        | 43.0  | 258  | 1.1358          | 0.6098   |
| 1.0281        | 44.0  | 264  | 1.1358          | 0.6098   |
| 1.0542        | 45.0  | 270  | 1.1358          | 0.6098   |
| 1.0542        | 46.0  | 276  | 1.1358          | 0.6098   |
| 1.0409        | 47.0  | 282  | 1.1358          | 0.6098   |
| 1.0409        | 48.0  | 288  | 1.1358          | 0.6098   |
| 1.0504        | 49.0  | 294  | 1.1358          | 0.6098   |
| 1.0111        | 50.0  | 300  | 1.1358          | 0.6098   |


### Framework versions

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