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# hushem_5x_deit_small_adamax_00001_fold4

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5172
- Accuracy: 0.8333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2786        | 1.0   | 28   | 1.2504          | 0.4286   |
| 1.0062        | 2.0   | 56   | 1.1218          | 0.4524   |
| 0.7412        | 3.0   | 84   | 0.9795          | 0.4762   |
| 0.5492        | 4.0   | 112  | 0.8870          | 0.6190   |
| 0.3717        | 5.0   | 140  | 0.7811          | 0.6667   |
| 0.3128        | 6.0   | 168  | 0.7165          | 0.7619   |
| 0.2014        | 7.0   | 196  | 0.6520          | 0.7143   |
| 0.169         | 8.0   | 224  | 0.6139          | 0.7143   |
| 0.0981        | 9.0   | 252  | 0.5693          | 0.7619   |
| 0.0593        | 10.0  | 280  | 0.5620          | 0.7381   |
| 0.0447        | 11.0  | 308  | 0.5082          | 0.8095   |
| 0.0256        | 12.0  | 336  | 0.4626          | 0.8333   |
| 0.0121        | 13.0  | 364  | 0.5351          | 0.7857   |
| 0.0073        | 14.0  | 392  | 0.4890          | 0.8333   |
| 0.0046        | 15.0  | 420  | 0.4933          | 0.8095   |
| 0.004         | 16.0  | 448  | 0.4823          | 0.8095   |
| 0.0033        | 17.0  | 476  | 0.4875          | 0.8095   |
| 0.0029        | 18.0  | 504  | 0.4984          | 0.8095   |
| 0.0023        | 19.0  | 532  | 0.4992          | 0.8095   |
| 0.0021        | 20.0  | 560  | 0.5018          | 0.8095   |
| 0.0018        | 21.0  | 588  | 0.4990          | 0.8095   |
| 0.0017        | 22.0  | 616  | 0.5045          | 0.8095   |
| 0.0014        | 23.0  | 644  | 0.5039          | 0.8095   |
| 0.0014        | 24.0  | 672  | 0.5120          | 0.8095   |
| 0.0013        | 25.0  | 700  | 0.5026          | 0.8095   |
| 0.0011        | 26.0  | 728  | 0.5060          | 0.8095   |
| 0.0012        | 27.0  | 756  | 0.5096          | 0.8095   |
| 0.0011        | 28.0  | 784  | 0.5088          | 0.8095   |
| 0.001         | 29.0  | 812  | 0.5017          | 0.8095   |
| 0.0009        | 30.0  | 840  | 0.5154          | 0.8095   |
| 0.001         | 31.0  | 868  | 0.5070          | 0.8095   |
| 0.0009        | 32.0  | 896  | 0.5093          | 0.8095   |
| 0.0009        | 33.0  | 924  | 0.5133          | 0.8095   |
| 0.0008        | 34.0  | 952  | 0.5115          | 0.8095   |
| 0.0008        | 35.0  | 980  | 0.5134          | 0.8095   |
| 0.0008        | 36.0  | 1008 | 0.5048          | 0.8333   |
| 0.0007        | 37.0  | 1036 | 0.5114          | 0.8095   |
| 0.0007        | 38.0  | 1064 | 0.5110          | 0.8333   |
| 0.0007        | 39.0  | 1092 | 0.5114          | 0.8333   |
| 0.0007        | 40.0  | 1120 | 0.5148          | 0.8333   |
| 0.0007        | 41.0  | 1148 | 0.5122          | 0.8333   |
| 0.0007        | 42.0  | 1176 | 0.5146          | 0.8333   |
| 0.0007        | 43.0  | 1204 | 0.5155          | 0.8333   |
| 0.0007        | 44.0  | 1232 | 0.5189          | 0.8333   |
| 0.0006        | 45.0  | 1260 | 0.5166          | 0.8333   |
| 0.0006        | 46.0  | 1288 | 0.5169          | 0.8333   |
| 0.0007        | 47.0  | 1316 | 0.5173          | 0.8333   |
| 0.0006        | 48.0  | 1344 | 0.5172          | 0.8333   |
| 0.0007        | 49.0  | 1372 | 0.5172          | 0.8333   |
| 0.0007        | 50.0  | 1400 | 0.5172          | 0.8333   |


### 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-small-patch16-224", "model-index": [{"name": "hushem_5x_deit_small_adamax_00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8333333333333334, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us