
<!-- 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_00001_fold4

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: 0.5330
- Accuracy: 0.7619

## 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    | 1.3484          | 0.2857   |
| 1.3393        | 2.0   | 12   | 1.3138          | 0.4524   |
| 1.3393        | 3.0   | 18   | 1.2772          | 0.4048   |
| 1.1604        | 4.0   | 24   | 1.2261          | 0.4524   |
| 1.014         | 5.0   | 30   | 1.1685          | 0.4762   |
| 1.014         | 6.0   | 36   | 1.1130          | 0.5476   |
| 0.8569        | 7.0   | 42   | 1.0641          | 0.5476   |
| 0.8569        | 8.0   | 48   | 1.0213          | 0.5476   |
| 0.7145        | 9.0   | 54   | 0.9685          | 0.5714   |
| 0.5812        | 10.0  | 60   | 0.9109          | 0.6190   |
| 0.5812        | 11.0  | 66   | 0.8739          | 0.6905   |
| 0.4645        | 12.0  | 72   | 0.8376          | 0.6667   |
| 0.4645        | 13.0  | 78   | 0.8046          | 0.6667   |
| 0.3784        | 14.0  | 84   | 0.7821          | 0.6667   |
| 0.308         | 15.0  | 90   | 0.7516          | 0.6905   |
| 0.308         | 16.0  | 96   | 0.7309          | 0.7143   |
| 0.2446        | 17.0  | 102  | 0.7113          | 0.7381   |
| 0.2446        | 18.0  | 108  | 0.6911          | 0.7143   |
| 0.2032        | 19.0  | 114  | 0.6782          | 0.6905   |
| 0.1713        | 20.0  | 120  | 0.6649          | 0.7381   |
| 0.1713        | 21.0  | 126  | 0.6459          | 0.7381   |
| 0.1338        | 22.0  | 132  | 0.6300          | 0.7143   |
| 0.1338        | 23.0  | 138  | 0.6291          | 0.7619   |
| 0.113         | 24.0  | 144  | 0.6105          | 0.8095   |
| 0.0989        | 25.0  | 150  | 0.5999          | 0.7619   |
| 0.0989        | 26.0  | 156  | 0.5962          | 0.7857   |
| 0.0793        | 27.0  | 162  | 0.5828          | 0.7619   |
| 0.0793        | 28.0  | 168  | 0.5775          | 0.7857   |
| 0.0704        | 29.0  | 174  | 0.5718          | 0.7857   |
| 0.0586        | 30.0  | 180  | 0.5598          | 0.7857   |
| 0.0586        | 31.0  | 186  | 0.5576          | 0.7857   |
| 0.0498        | 32.0  | 192  | 0.5530          | 0.7857   |
| 0.0498        | 33.0  | 198  | 0.5470          | 0.7857   |
| 0.0487        | 34.0  | 204  | 0.5432          | 0.7857   |
| 0.0426        | 35.0  | 210  | 0.5430          | 0.7619   |
| 0.0426        | 36.0  | 216  | 0.5406          | 0.7619   |
| 0.0394        | 37.0  | 222  | 0.5370          | 0.7619   |
| 0.0394        | 38.0  | 228  | 0.5337          | 0.7619   |
| 0.039         | 39.0  | 234  | 0.5328          | 0.7619   |
| 0.0365        | 40.0  | 240  | 0.5330          | 0.7619   |
| 0.0365        | 41.0  | 246  | 0.5331          | 0.7619   |
| 0.0366        | 42.0  | 252  | 0.5330          | 0.7619   |
| 0.0366        | 43.0  | 258  | 0.5330          | 0.7619   |
| 0.0347        | 44.0  | 264  | 0.5330          | 0.7619   |
| 0.0374        | 45.0  | 270  | 0.5330          | 0.7619   |
| 0.0374        | 46.0  | 276  | 0.5330          | 0.7619   |
| 0.0363        | 47.0  | 282  | 0.5330          | 0.7619   |
| 0.0363        | 48.0  | 288  | 0.5330          | 0.7619   |
| 0.0346        | 49.0  | 294  | 0.5330          | 0.7619   |
| 0.0366        | 50.0  | 300  | 0.5330          | 0.7619   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "hushem_1x_deit_base_adamax_00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7619047619047619, "name": "Accuracy"}]}]}]}
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