transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_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: 0.6341463414634146
---

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# hushem_1x_deit_base_rms_0001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3526
- Accuracy: 0.6341

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.7430          | 0.2683   |
| 1.6349        | 2.0   | 12   | 1.4230          | 0.2683   |
| 1.6349        | 3.0   | 18   | 1.4257          | 0.2439   |
| 1.5924        | 4.0   | 24   | 1.4051          | 0.2683   |
| 1.3846        | 5.0   | 30   | 1.3194          | 0.4390   |
| 1.3846        | 6.0   | 36   | 1.3419          | 0.2683   |
| 1.3811        | 7.0   | 42   | 1.2559          | 0.3659   |
| 1.3811        | 8.0   | 48   | 1.3108          | 0.3659   |
| 1.2606        | 9.0   | 54   | 1.1795          | 0.4390   |
| 1.2777        | 10.0  | 60   | 1.0431          | 0.6098   |
| 1.2777        | 11.0  | 66   | 1.0339          | 0.5854   |
| 1.0645        | 12.0  | 72   | 1.0817          | 0.3659   |
| 1.0645        | 13.0  | 78   | 1.1465          | 0.5366   |
| 0.9095        | 14.0  | 84   | 1.5053          | 0.4390   |
| 0.565         | 15.0  | 90   | 1.1416          | 0.5610   |
| 0.565         | 16.0  | 96   | 2.1735          | 0.4390   |
| 0.3519        | 17.0  | 102  | 2.3494          | 0.4878   |
| 0.3519        | 18.0  | 108  | 1.4016          | 0.5854   |
| 0.1942        | 19.0  | 114  | 2.3483          | 0.5854   |
| 0.0922        | 20.0  | 120  | 2.0423          | 0.6585   |
| 0.0922        | 21.0  | 126  | 2.0605          | 0.6098   |
| 0.0726        | 22.0  | 132  | 2.1739          | 0.6098   |
| 0.0726        | 23.0  | 138  | 2.2024          | 0.6098   |
| 0.0015        | 24.0  | 144  | 2.2222          | 0.6098   |
| 0.0005        | 25.0  | 150  | 2.2407          | 0.6098   |
| 0.0005        | 26.0  | 156  | 2.2567          | 0.6098   |
| 0.0005        | 27.0  | 162  | 2.2698          | 0.6098   |
| 0.0005        | 28.0  | 168  | 2.2828          | 0.6341   |
| 0.0004        | 29.0  | 174  | 2.2925          | 0.6341   |
| 0.0003        | 30.0  | 180  | 2.3020          | 0.6341   |
| 0.0003        | 31.0  | 186  | 2.3104          | 0.6341   |
| 0.0003        | 32.0  | 192  | 2.3179          | 0.6341   |
| 0.0003        | 33.0  | 198  | 2.3248          | 0.6341   |
| 0.0002        | 34.0  | 204  | 2.3308          | 0.6341   |
| 0.0003        | 35.0  | 210  | 2.3358          | 0.6341   |
| 0.0003        | 36.0  | 216  | 2.3401          | 0.6341   |
| 0.0002        | 37.0  | 222  | 2.3438          | 0.6341   |
| 0.0002        | 38.0  | 228  | 2.3470          | 0.6341   |
| 0.0002        | 39.0  | 234  | 2.3496          | 0.6341   |
| 0.0002        | 40.0  | 240  | 2.3513          | 0.6341   |
| 0.0002        | 41.0  | 246  | 2.3523          | 0.6341   |
| 0.0002        | 42.0  | 252  | 2.3526          | 0.6341   |
| 0.0002        | 43.0  | 258  | 2.3526          | 0.6341   |
| 0.0002        | 44.0  | 264  | 2.3526          | 0.6341   |
| 0.0002        | 45.0  | 270  | 2.3526          | 0.6341   |
| 0.0002        | 46.0  | 276  | 2.3526          | 0.6341   |
| 0.0002        | 47.0  | 282  | 2.3526          | 0.6341   |
| 0.0002        | 48.0  | 288  | 2.3526          | 0.6341   |
| 0.0002        | 49.0  | 294  | 2.3526          | 0.6341   |
| 0.0002        | 50.0  | 300  | 2.3526          | 0.6341   |


### Framework versions

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