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_adamax_0001_fold1
  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: 0.7555555555555555
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_1x_deit_base_adamax_0001_fold1

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: 1.0735
- Accuracy: 0.7556

## 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    | 1.2850          | 0.3333   |
| 1.0598        | 2.0   | 12   | 0.9334          | 0.6889   |
| 1.0598        | 3.0   | 18   | 0.8053          | 0.7333   |
| 0.3175        | 4.0   | 24   | 0.8711          | 0.6444   |
| 0.0445        | 5.0   | 30   | 0.8608          | 0.7556   |
| 0.0445        | 6.0   | 36   | 0.7787          | 0.7778   |
| 0.0064        | 7.0   | 42   | 0.8229          | 0.7111   |
| 0.0064        | 8.0   | 48   | 0.9560          | 0.6667   |
| 0.0019        | 9.0   | 54   | 1.0123          | 0.7111   |
| 0.001         | 10.0  | 60   | 1.0574          | 0.7111   |
| 0.001         | 11.0  | 66   | 1.0683          | 0.7111   |
| 0.0007        | 12.0  | 72   | 1.0663          | 0.7111   |
| 0.0007        | 13.0  | 78   | 1.0586          | 0.7111   |
| 0.0005        | 14.0  | 84   | 1.0513          | 0.7333   |
| 0.0005        | 15.0  | 90   | 1.0471          | 0.7333   |
| 0.0005        | 16.0  | 96   | 1.0473          | 0.7333   |
| 0.0004        | 17.0  | 102  | 1.0477          | 0.7333   |
| 0.0004        | 18.0  | 108  | 1.0472          | 0.7333   |
| 0.0004        | 19.0  | 114  | 1.0473          | 0.7333   |
| 0.0004        | 20.0  | 120  | 1.0490          | 0.7556   |
| 0.0004        | 21.0  | 126  | 1.0517          | 0.7556   |
| 0.0004        | 22.0  | 132  | 1.0538          | 0.7556   |
| 0.0004        | 23.0  | 138  | 1.0557          | 0.7556   |
| 0.0003        | 24.0  | 144  | 1.0576          | 0.7556   |
| 0.0003        | 25.0  | 150  | 1.0597          | 0.7556   |
| 0.0003        | 26.0  | 156  | 1.0622          | 0.7556   |
| 0.0003        | 27.0  | 162  | 1.0623          | 0.7556   |
| 0.0003        | 28.0  | 168  | 1.0636          | 0.7556   |
| 0.0003        | 29.0  | 174  | 1.0651          | 0.7556   |
| 0.0003        | 30.0  | 180  | 1.0659          | 0.7556   |
| 0.0003        | 31.0  | 186  | 1.0671          | 0.7556   |
| 0.0003        | 32.0  | 192  | 1.0678          | 0.7556   |
| 0.0003        | 33.0  | 198  | 1.0692          | 0.7556   |
| 0.0003        | 34.0  | 204  | 1.0702          | 0.7556   |
| 0.0003        | 35.0  | 210  | 1.0706          | 0.7556   |
| 0.0003        | 36.0  | 216  | 1.0707          | 0.7556   |
| 0.0003        | 37.0  | 222  | 1.0711          | 0.7556   |
| 0.0003        | 38.0  | 228  | 1.0722          | 0.7556   |
| 0.0003        | 39.0  | 234  | 1.0729          | 0.7556   |
| 0.0003        | 40.0  | 240  | 1.0733          | 0.7556   |
| 0.0003        | 41.0  | 246  | 1.0735          | 0.7556   |
| 0.0003        | 42.0  | 252  | 1.0735          | 0.7556   |
| 0.0003        | 43.0  | 258  | 1.0735          | 0.7556   |
| 0.0003        | 44.0  | 264  | 1.0735          | 0.7556   |
| 0.0003        | 45.0  | 270  | 1.0735          | 0.7556   |
| 0.0003        | 46.0  | 276  | 1.0735          | 0.7556   |
| 0.0003        | 47.0  | 282  | 1.0735          | 0.7556   |
| 0.0003        | 48.0  | 288  | 1.0735          | 0.7556   |
| 0.0003        | 49.0  | 294  | 1.0735          | 0.7556   |
| 0.0003        | 50.0  | 300  | 1.0735          | 0.7556   |


### Framework versions

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