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# hushem_5x_deit_tiny_rms_001_fold5

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: 1.8130
- Accuracy: 0.6098

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7861        | 1.0   | 28   | 1.6178          | 0.2439   |
| 1.5274        | 2.0   | 56   | 1.5079          | 0.2683   |
| 1.4754        | 3.0   | 84   | 1.5602          | 0.2439   |
| 1.4772        | 4.0   | 112  | 1.4942          | 0.2683   |
| 1.3612        | 5.0   | 140  | 1.2123          | 0.4146   |
| 1.3875        | 6.0   | 168  | 1.3792          | 0.3415   |
| 1.2469        | 7.0   | 196  | 1.2932          | 0.3171   |
| 1.2171        | 8.0   | 224  | 1.2748          | 0.3902   |
| 1.2175        | 9.0   | 252  | 1.1348          | 0.4390   |
| 1.166         | 10.0  | 280  | 1.0946          | 0.4878   |
| 1.164         | 11.0  | 308  | 0.8922          | 0.6829   |
| 1.0132        | 12.0  | 336  | 0.8702          | 0.7317   |
| 1.0418        | 13.0  | 364  | 1.2510          | 0.5366   |
| 0.9219        | 14.0  | 392  | 0.9079          | 0.5854   |
| 0.9159        | 15.0  | 420  | 1.0015          | 0.5366   |
| 0.9295        | 16.0  | 448  | 0.9465          | 0.6829   |
| 0.8951        | 17.0  | 476  | 0.9426          | 0.6585   |
| 0.8137        | 18.0  | 504  | 0.9329          | 0.6098   |
| 0.8716        | 19.0  | 532  | 0.8386          | 0.7073   |
| 1.0116        | 20.0  | 560  | 0.7967          | 0.7073   |
| 0.8813        | 21.0  | 588  | 0.8366          | 0.7561   |
| 0.8835        | 22.0  | 616  | 1.0236          | 0.7073   |
| 0.8442        | 23.0  | 644  | 0.8949          | 0.5366   |
| 0.7804        | 24.0  | 672  | 0.9501          | 0.6829   |
| 0.7587        | 25.0  | 700  | 0.8384          | 0.6829   |
| 0.6929        | 26.0  | 728  | 0.9426          | 0.6098   |
| 0.7631        | 27.0  | 756  | 0.9144          | 0.6829   |
| 0.7309        | 28.0  | 784  | 0.8469          | 0.7317   |
| 0.6928        | 29.0  | 812  | 0.8593          | 0.6341   |
| 0.7758        | 30.0  | 840  | 0.8452          | 0.7561   |
| 0.6741        | 31.0  | 868  | 0.6468          | 0.7317   |
| 0.6387        | 32.0  | 896  | 0.8346          | 0.7317   |
| 0.6393        | 33.0  | 924  | 0.9678          | 0.7073   |
| 0.6388        | 34.0  | 952  | 0.9404          | 0.7317   |
| 0.5553        | 35.0  | 980  | 0.9751          | 0.6829   |
| 0.5488        | 36.0  | 1008 | 0.8789          | 0.6829   |
| 0.5749        | 37.0  | 1036 | 0.9082          | 0.6829   |
| 0.5631        | 38.0  | 1064 | 1.0681          | 0.6829   |
| 0.5744        | 39.0  | 1092 | 1.0203          | 0.6341   |
| 0.4507        | 40.0  | 1120 | 1.0247          | 0.6341   |
| 0.4706        | 41.0  | 1148 | 1.0726          | 0.6585   |
| 0.2984        | 42.0  | 1176 | 1.3959          | 0.6585   |
| 0.3096        | 43.0  | 1204 | 1.3220          | 0.6098   |
| 0.3345        | 44.0  | 1232 | 1.8003          | 0.6341   |
| 0.2779        | 45.0  | 1260 | 1.6742          | 0.6098   |
| 0.2186        | 46.0  | 1288 | 1.6974          | 0.6098   |
| 0.2223        | 47.0  | 1316 | 1.8144          | 0.6098   |
| 0.1904        | 48.0  | 1344 | 1.8092          | 0.6098   |
| 0.1904        | 49.0  | 1372 | 1.8130          | 0.6098   |
| 0.1964        | 50.0  | 1400 | 1.8130          | 0.6098   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-tiny-patch16-224", "model-index": [{"name": "hushem_5x_deit_tiny_rms_001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6097560975609756, "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