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# hushem_1x_deit_tiny_rms_0001_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: 3.4166
- Accuracy: 0.5556

## 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    | 2.1314          | 0.2444   |
| 2.0481        | 2.0   | 12   | 1.5573          | 0.2444   |
| 2.0481        | 3.0   | 18   | 1.4598          | 0.2444   |
| 1.5099        | 4.0   | 24   | 1.4194          | 0.2444   |
| 1.4253        | 5.0   | 30   | 1.3528          | 0.2667   |
| 1.4253        | 6.0   | 36   | 1.6348          | 0.2444   |
| 1.3319        | 7.0   | 42   | 1.3901          | 0.4444   |
| 1.3319        | 8.0   | 48   | 1.3151          | 0.2889   |
| 1.2142        | 9.0   | 54   | 1.3395          | 0.3333   |
| 1.1416        | 10.0  | 60   | 1.4176          | 0.3556   |
| 1.1416        | 11.0  | 66   | 1.9072          | 0.2667   |
| 0.9889        | 12.0  | 72   | 1.7446          | 0.3111   |
| 0.9889        | 13.0  | 78   | 1.4748          | 0.3778   |
| 0.8552        | 14.0  | 84   | 1.7450          | 0.3778   |
| 0.6798        | 15.0  | 90   | 1.6042          | 0.4889   |
| 0.6798        | 16.0  | 96   | 1.5863          | 0.4222   |
| 0.563         | 17.0  | 102  | 1.9311          | 0.4      |
| 0.563         | 18.0  | 108  | 1.9509          | 0.4444   |
| 0.3845        | 19.0  | 114  | 2.1256          | 0.4667   |
| 0.2041        | 20.0  | 120  | 2.4131          | 0.4889   |
| 0.2041        | 21.0  | 126  | 2.1029          | 0.4667   |
| 0.1874        | 22.0  | 132  | 2.0412          | 0.5778   |
| 0.1874        | 23.0  | 138  | 2.4952          | 0.4889   |
| 0.0735        | 24.0  | 144  | 2.8992          | 0.4667   |
| 0.0229        | 25.0  | 150  | 2.7495          | 0.5556   |
| 0.0229        | 26.0  | 156  | 3.2879          | 0.4667   |
| 0.0293        | 27.0  | 162  | 3.1526          | 0.5111   |
| 0.0293        | 28.0  | 168  | 3.0123          | 0.5333   |
| 0.0023        | 29.0  | 174  | 3.0812          | 0.5556   |
| 0.0008        | 30.0  | 180  | 3.1384          | 0.5556   |
| 0.0008        | 31.0  | 186  | 3.2017          | 0.5556   |
| 0.0005        | 32.0  | 192  | 3.2443          | 0.5556   |
| 0.0005        | 33.0  | 198  | 3.2806          | 0.5556   |
| 0.0005        | 34.0  | 204  | 3.3167          | 0.5556   |
| 0.0004        | 35.0  | 210  | 3.3393          | 0.5556   |
| 0.0004        | 36.0  | 216  | 3.3662          | 0.5556   |
| 0.0004        | 37.0  | 222  | 3.3843          | 0.5556   |
| 0.0004        | 38.0  | 228  | 3.3970          | 0.5556   |
| 0.0003        | 39.0  | 234  | 3.4053          | 0.5556   |
| 0.0003        | 40.0  | 240  | 3.4123          | 0.5556   |
| 0.0003        | 41.0  | 246  | 3.4159          | 0.5556   |
| 0.0003        | 42.0  | 252  | 3.4166          | 0.5556   |
| 0.0003        | 43.0  | 258  | 3.4166          | 0.5556   |
| 0.0003        | 44.0  | 264  | 3.4166          | 0.5556   |
| 0.0003        | 45.0  | 270  | 3.4166          | 0.5556   |
| 0.0003        | 46.0  | 276  | 3.4166          | 0.5556   |
| 0.0003        | 47.0  | 282  | 3.4166          | 0.5556   |
| 0.0003        | 48.0  | 288  | 3.4166          | 0.5556   |
| 0.0003        | 49.0  | 294  | 3.4166          | 0.5556   |
| 0.0003        | 50.0  | 300  | 3.4166          | 0.5556   |


### 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_0001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5555555555555556, "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