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_rms_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: 0.8095238095238095
---

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# hushem_1x_deit_small_rms_00001_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: 0.4388
- Accuracy: 0.8095

## 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    | 1.2550          | 0.4286   |
| 1.2114        | 2.0   | 12   | 1.1127          | 0.4762   |
| 1.2114        | 3.0   | 18   | 0.8436          | 0.6667   |
| 0.6039        | 4.0   | 24   | 0.7891          | 0.6429   |
| 0.2289        | 5.0   | 30   | 0.6119          | 0.7143   |
| 0.2289        | 6.0   | 36   | 0.5730          | 0.7381   |
| 0.0572        | 7.0   | 42   | 0.5854          | 0.7381   |
| 0.0572        | 8.0   | 48   | 0.4823          | 0.7619   |
| 0.0155        | 9.0   | 54   | 0.4273          | 0.8095   |
| 0.0057        | 10.0  | 60   | 0.4459          | 0.8095   |
| 0.0057        | 11.0  | 66   | 0.4283          | 0.8333   |
| 0.0036        | 12.0  | 72   | 0.4439          | 0.8333   |
| 0.0036        | 13.0  | 78   | 0.4381          | 0.8333   |
| 0.0028        | 14.0  | 84   | 0.4361          | 0.8095   |
| 0.0022        | 15.0  | 90   | 0.4297          | 0.8095   |
| 0.0022        | 16.0  | 96   | 0.4286          | 0.8333   |
| 0.0018        | 17.0  | 102  | 0.4333          | 0.8333   |
| 0.0018        | 18.0  | 108  | 0.4303          | 0.8333   |
| 0.0015        | 19.0  | 114  | 0.4275          | 0.8095   |
| 0.0014        | 20.0  | 120  | 0.4353          | 0.8095   |
| 0.0014        | 21.0  | 126  | 0.4311          | 0.8095   |
| 0.0012        | 22.0  | 132  | 0.4354          | 0.8095   |
| 0.0012        | 23.0  | 138  | 0.4378          | 0.8095   |
| 0.0011        | 24.0  | 144  | 0.4372          | 0.8095   |
| 0.001         | 25.0  | 150  | 0.4362          | 0.8095   |
| 0.001         | 26.0  | 156  | 0.4357          | 0.8095   |
| 0.0009        | 27.0  | 162  | 0.4417          | 0.8095   |
| 0.0009        | 28.0  | 168  | 0.4425          | 0.8095   |
| 0.0009        | 29.0  | 174  | 0.4408          | 0.8095   |
| 0.0008        | 30.0  | 180  | 0.4402          | 0.8095   |
| 0.0008        | 31.0  | 186  | 0.4406          | 0.8095   |
| 0.0008        | 32.0  | 192  | 0.4385          | 0.8095   |
| 0.0008        | 33.0  | 198  | 0.4397          | 0.8095   |
| 0.0007        | 34.0  | 204  | 0.4393          | 0.8095   |
| 0.0007        | 35.0  | 210  | 0.4395          | 0.8095   |
| 0.0007        | 36.0  | 216  | 0.4391          | 0.8095   |
| 0.0007        | 37.0  | 222  | 0.4387          | 0.8095   |
| 0.0007        | 38.0  | 228  | 0.4386          | 0.8095   |
| 0.0007        | 39.0  | 234  | 0.4388          | 0.8095   |
| 0.0007        | 40.0  | 240  | 0.4387          | 0.8095   |
| 0.0007        | 41.0  | 246  | 0.4388          | 0.8095   |
| 0.0007        | 42.0  | 252  | 0.4388          | 0.8095   |
| 0.0007        | 43.0  | 258  | 0.4388          | 0.8095   |
| 0.0006        | 44.0  | 264  | 0.4388          | 0.8095   |
| 0.0007        | 45.0  | 270  | 0.4388          | 0.8095   |
| 0.0007        | 46.0  | 276  | 0.4388          | 0.8095   |
| 0.0007        | 47.0  | 282  | 0.4388          | 0.8095   |
| 0.0007        | 48.0  | 288  | 0.4388          | 0.8095   |
| 0.0006        | 49.0  | 294  | 0.4388          | 0.8095   |
| 0.0007        | 50.0  | 300  | 0.4388          | 0.8095   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
