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# hushem_1x_deit_base_adamax_001_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: 2.6471
- Accuracy: 0.5952

## 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    | 1.4889          | 0.2381   |
| 1.6928        | 2.0   | 12   | 1.4102          | 0.2381   |
| 1.6928        | 3.0   | 18   | 1.2949          | 0.4048   |
| 1.4466        | 4.0   | 24   | 1.1224          | 0.4762   |
| 1.3026        | 5.0   | 30   | 1.3079          | 0.3333   |
| 1.3026        | 6.0   | 36   | 1.0368          | 0.6190   |
| 1.2798        | 7.0   | 42   | 1.2143          | 0.3571   |
| 1.2798        | 8.0   | 48   | 1.0732          | 0.5      |
| 1.1914        | 9.0   | 54   | 1.0366          | 0.5476   |
| 1.2164        | 10.0  | 60   | 1.0675          | 0.5      |
| 1.2164        | 11.0  | 66   | 1.0841          | 0.4762   |
| 1.2177        | 12.0  | 72   | 1.1092          | 0.5952   |
| 1.2177        | 13.0  | 78   | 0.9871          | 0.5238   |
| 1.183         | 14.0  | 84   | 1.1380          | 0.4762   |
| 1.2146        | 15.0  | 90   | 1.1128          | 0.5      |
| 1.2146        | 16.0  | 96   | 0.9957          | 0.5952   |
| 1.1103        | 17.0  | 102  | 1.0192          | 0.5952   |
| 1.1103        | 18.0  | 108  | 1.1751          | 0.5      |
| 1.0656        | 19.0  | 114  | 1.1301          | 0.5      |
| 1.047         | 20.0  | 120  | 1.1327          | 0.4048   |
| 1.047         | 21.0  | 126  | 1.2359          | 0.4762   |
| 0.8853        | 22.0  | 132  | 1.1524          | 0.5952   |
| 0.8853        | 23.0  | 138  | 1.9551          | 0.3095   |
| 0.7611        | 24.0  | 144  | 1.3513          | 0.5      |
| 0.7727        | 25.0  | 150  | 1.6490          | 0.5476   |
| 0.7727        | 26.0  | 156  | 1.0702          | 0.4048   |
| 0.8546        | 27.0  | 162  | 1.7107          | 0.3333   |
| 0.8546        | 28.0  | 168  | 1.3302          | 0.4286   |
| 0.695         | 29.0  | 174  | 1.1947          | 0.5714   |
| 0.4593        | 30.0  | 180  | 1.8330          | 0.4762   |
| 0.4593        | 31.0  | 186  | 1.6031          | 0.5952   |
| 0.2978        | 32.0  | 192  | 2.1238          | 0.6190   |
| 0.2978        | 33.0  | 198  | 2.3897          | 0.5476   |
| 0.2625        | 34.0  | 204  | 2.1147          | 0.6190   |
| 0.1062        | 35.0  | 210  | 2.6950          | 0.5      |
| 0.1062        | 36.0  | 216  | 2.5016          | 0.6190   |
| 0.0682        | 37.0  | 222  | 2.6327          | 0.5476   |
| 0.0682        | 38.0  | 228  | 2.5000          | 0.5714   |
| 0.0309        | 39.0  | 234  | 2.4431          | 0.6190   |
| 0.019         | 40.0  | 240  | 2.6997          | 0.5714   |
| 0.019         | 41.0  | 246  | 2.6710          | 0.5952   |
| 0.0078        | 42.0  | 252  | 2.6471          | 0.5952   |
| 0.0078        | 43.0  | 258  | 2.6471          | 0.5952   |
| 0.0071        | 44.0  | 264  | 2.6471          | 0.5952   |
| 0.0054        | 45.0  | 270  | 2.6471          | 0.5952   |
| 0.0054        | 46.0  | 276  | 2.6471          | 0.5952   |
| 0.0076        | 47.0  | 282  | 2.6471          | 0.5952   |
| 0.0076        | 48.0  | 288  | 2.6471          | 0.5952   |
| 0.0053        | 49.0  | 294  | 2.6471          | 0.5952   |
| 0.0059        | 50.0  | 300  | 2.6471          | 0.5952   |


### Framework versions

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

{"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_001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5952380952380952, "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