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# hushem_1x_deit_tiny_rms_00001_fold1

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2620
- Accuracy: 0.6222

## 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    | 1.3330          | 0.3111   |
| 1.415         | 2.0   | 12   | 1.1496          | 0.4222   |
| 1.415         | 3.0   | 18   | 1.0095          | 0.6      |
| 0.6844        | 4.0   | 24   | 1.0528          | 0.5333   |
| 0.3289        | 5.0   | 30   | 0.8970          | 0.6      |
| 0.3289        | 6.0   | 36   | 1.2025          | 0.5111   |
| 0.1275        | 7.0   | 42   | 0.9016          | 0.6      |
| 0.1275        | 8.0   | 48   | 1.0450          | 0.5778   |
| 0.049         | 9.0   | 54   | 1.1767          | 0.5556   |
| 0.0201        | 10.0  | 60   | 1.2285          | 0.5333   |
| 0.0201        | 11.0  | 66   | 1.0471          | 0.6      |
| 0.0071        | 12.0  | 72   | 0.9300          | 0.6444   |
| 0.0071        | 13.0  | 78   | 1.1280          | 0.5778   |
| 0.0042        | 14.0  | 84   | 1.1318          | 0.5556   |
| 0.0029        | 15.0  | 90   | 1.1503          | 0.5556   |
| 0.0029        | 16.0  | 96   | 1.0998          | 0.5778   |
| 0.0023        | 17.0  | 102  | 1.1889          | 0.5778   |
| 0.0023        | 18.0  | 108  | 1.2431          | 0.5778   |
| 0.0018        | 19.0  | 114  | 1.2158          | 0.5778   |
| 0.0016        | 20.0  | 120  | 1.2220          | 0.6      |
| 0.0016        | 21.0  | 126  | 1.1974          | 0.6      |
| 0.0014        | 22.0  | 132  | 1.2207          | 0.6      |
| 0.0014        | 23.0  | 138  | 1.2242          | 0.6      |
| 0.0013        | 24.0  | 144  | 1.2118          | 0.6      |
| 0.0011        | 25.0  | 150  | 1.2264          | 0.6222   |
| 0.0011        | 26.0  | 156  | 1.2250          | 0.6      |
| 0.0011        | 27.0  | 162  | 1.2237          | 0.6      |
| 0.0011        | 28.0  | 168  | 1.2290          | 0.6      |
| 0.001         | 29.0  | 174  | 1.2254          | 0.6222   |
| 0.0009        | 30.0  | 180  | 1.2294          | 0.6222   |
| 0.0009        | 31.0  | 186  | 1.2336          | 0.6222   |
| 0.0009        | 32.0  | 192  | 1.2394          | 0.6222   |
| 0.0009        | 33.0  | 198  | 1.2441          | 0.6222   |
| 0.0008        | 34.0  | 204  | 1.2483          | 0.6      |
| 0.0008        | 35.0  | 210  | 1.2484          | 0.6      |
| 0.0008        | 36.0  | 216  | 1.2564          | 0.6      |
| 0.0008        | 37.0  | 222  | 1.2583          | 0.6222   |
| 0.0008        | 38.0  | 228  | 1.2617          | 0.6222   |
| 0.0007        | 39.0  | 234  | 1.2626          | 0.6222   |
| 0.0007        | 40.0  | 240  | 1.2627          | 0.6222   |
| 0.0007        | 41.0  | 246  | 1.2621          | 0.6222   |
| 0.0007        | 42.0  | 252  | 1.2620          | 0.6222   |
| 0.0007        | 43.0  | 258  | 1.2620          | 0.6222   |
| 0.0007        | 44.0  | 264  | 1.2620          | 0.6222   |
| 0.0007        | 45.0  | 270  | 1.2620          | 0.6222   |
| 0.0007        | 46.0  | 276  | 1.2620          | 0.6222   |
| 0.0007        | 47.0  | 282  | 1.2620          | 0.6222   |
| 0.0007        | 48.0  | 288  | 1.2620          | 0.6222   |
| 0.0007        | 49.0  | 294  | 1.2620          | 0.6222   |
| 0.0007        | 50.0  | 300  | 1.2620          | 0.6222   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_1x_deit_tiny_rms_00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6222222222222222, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us