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# hushem_5x_deit_tiny_rms_001_fold4

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: 1.2679
- Accuracy: 0.6905

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1506        | 1.0   | 28   | 2.1514          | 0.2381   |
| 1.4805        | 2.0   | 56   | 1.6187          | 0.2619   |
| 1.4792        | 3.0   | 84   | 1.5112          | 0.2619   |
| 1.5148        | 4.0   | 112  | 1.3546          | 0.3095   |
| 1.3804        | 5.0   | 140  | 1.3723          | 0.4286   |
| 1.4296        | 6.0   | 168  | 1.1490          | 0.4048   |
| 1.1847        | 7.0   | 196  | 1.3299          | 0.4524   |
| 1.1564        | 8.0   | 224  | 1.0799          | 0.4762   |
| 1.0992        | 9.0   | 252  | 1.1631          | 0.5      |
| 1.0863        | 10.0  | 280  | 1.1300          | 0.4524   |
| 1.0126        | 11.0  | 308  | 0.9131          | 0.5      |
| 1.0272        | 12.0  | 336  | 0.9239          | 0.5      |
| 0.9747        | 13.0  | 364  | 0.9521          | 0.6667   |
| 0.9219        | 14.0  | 392  | 0.8729          | 0.7619   |
| 0.8522        | 15.0  | 420  | 0.6286          | 0.7381   |
| 0.8968        | 16.0  | 448  | 0.8515          | 0.6429   |
| 0.8266        | 17.0  | 476  | 0.8301          | 0.6429   |
| 0.8581        | 18.0  | 504  | 1.0046          | 0.5476   |
| 0.8265        | 19.0  | 532  | 0.8082          | 0.6429   |
| 0.8594        | 20.0  | 560  | 0.8196          | 0.6190   |
| 0.7439        | 21.0  | 588  | 0.7591          | 0.6190   |
| 0.7899        | 22.0  | 616  | 0.8303          | 0.5952   |
| 0.8223        | 23.0  | 644  | 0.6299          | 0.7143   |
| 0.8203        | 24.0  | 672  | 0.7361          | 0.7143   |
| 0.7414        | 25.0  | 700  | 0.7251          | 0.7143   |
| 0.6879        | 26.0  | 728  | 0.8771          | 0.6905   |
| 0.8008        | 27.0  | 756  | 0.8469          | 0.5714   |
| 0.7402        | 28.0  | 784  | 0.6058          | 0.7857   |
| 0.7223        | 29.0  | 812  | 0.8210          | 0.6905   |
| 0.7302        | 30.0  | 840  | 0.8614          | 0.7143   |
| 0.7098        | 31.0  | 868  | 0.9312          | 0.7143   |
| 0.7044        | 32.0  | 896  | 0.8159          | 0.7143   |
| 0.7096        | 33.0  | 924  | 0.9197          | 0.6905   |
| 0.6854        | 34.0  | 952  | 0.8631          | 0.6190   |
| 0.7442        | 35.0  | 980  | 0.8324          | 0.6667   |
| 0.6271        | 36.0  | 1008 | 0.8632          | 0.7381   |
| 0.6052        | 37.0  | 1036 | 0.8753          | 0.7143   |
| 0.6189        | 38.0  | 1064 | 1.0917          | 0.7381   |
| 0.5817        | 39.0  | 1092 | 0.9635          | 0.6429   |
| 0.5324        | 40.0  | 1120 | 1.0245          | 0.6667   |
| 0.5312        | 41.0  | 1148 | 1.1733          | 0.6905   |
| 0.5538        | 42.0  | 1176 | 1.0809          | 0.7143   |
| 0.4355        | 43.0  | 1204 | 1.0395          | 0.6667   |
| 0.3909        | 44.0  | 1232 | 1.1631          | 0.6667   |
| 0.301         | 45.0  | 1260 | 1.2110          | 0.6667   |
| 0.3678        | 46.0  | 1288 | 1.2357          | 0.6905   |
| 0.3355        | 47.0  | 1316 | 1.2487          | 0.7143   |
| 0.2983        | 48.0  | 1344 | 1.2713          | 0.6905   |
| 0.2527        | 49.0  | 1372 | 1.2679          | 0.6905   |
| 0.2761        | 50.0  | 1400 | 1.2679          | 0.6905   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6904761904761905, "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