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# hushem_5x_deit_tiny_adamax_00001_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: 0.4803
- Accuracy: 0.7857

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3199        | 1.0   | 28   | 1.2249          | 0.5      |
| 1.0134        | 2.0   | 56   | 1.0887          | 0.5476   |
| 0.8677        | 3.0   | 84   | 1.0102          | 0.6190   |
| 0.708         | 4.0   | 112  | 0.9014          | 0.5952   |
| 0.5921        | 5.0   | 140  | 0.8309          | 0.6429   |
| 0.5207        | 6.0   | 168  | 0.7657          | 0.6905   |
| 0.3875        | 7.0   | 196  | 0.7178          | 0.6667   |
| 0.3518        | 8.0   | 224  | 0.6618          | 0.6667   |
| 0.2677        | 9.0   | 252  | 0.6279          | 0.7143   |
| 0.2022        | 10.0  | 280  | 0.5907          | 0.7381   |
| 0.2088        | 11.0  | 308  | 0.5564          | 0.7857   |
| 0.1641        | 12.0  | 336  | 0.5320          | 0.7857   |
| 0.1049        | 13.0  | 364  | 0.5289          | 0.7857   |
| 0.092         | 14.0  | 392  | 0.5023          | 0.8095   |
| 0.0557        | 15.0  | 420  | 0.4953          | 0.7381   |
| 0.0471        | 16.0  | 448  | 0.4998          | 0.7857   |
| 0.0348        | 17.0  | 476  | 0.4480          | 0.8095   |
| 0.0266        | 18.0  | 504  | 0.4459          | 0.7857   |
| 0.0161        | 19.0  | 532  | 0.4594          | 0.7857   |
| 0.0135        | 20.0  | 560  | 0.4976          | 0.7619   |
| 0.0093        | 21.0  | 588  | 0.4434          | 0.7619   |
| 0.0077        | 22.0  | 616  | 0.4474          | 0.7619   |
| 0.0056        | 23.0  | 644  | 0.4598          | 0.7143   |
| 0.0046        | 24.0  | 672  | 0.4362          | 0.7381   |
| 0.0037        | 25.0  | 700  | 0.4189          | 0.7857   |
| 0.0032        | 26.0  | 728  | 0.4491          | 0.7857   |
| 0.0028        | 27.0  | 756  | 0.4480          | 0.7857   |
| 0.0026        | 28.0  | 784  | 0.4540          | 0.7857   |
| 0.0022        | 29.0  | 812  | 0.4510          | 0.7857   |
| 0.0021        | 30.0  | 840  | 0.4557          | 0.8095   |
| 0.0018        | 31.0  | 868  | 0.4556          | 0.7857   |
| 0.0017        | 32.0  | 896  | 0.4590          | 0.8095   |
| 0.0016        | 33.0  | 924  | 0.4610          | 0.8095   |
| 0.0015        | 34.0  | 952  | 0.4618          | 0.8095   |
| 0.0015        | 35.0  | 980  | 0.4661          | 0.8095   |
| 0.0013        | 36.0  | 1008 | 0.4626          | 0.8095   |
| 0.0012        | 37.0  | 1036 | 0.4685          | 0.8095   |
| 0.0013        | 38.0  | 1064 | 0.4710          | 0.8095   |
| 0.0012        | 39.0  | 1092 | 0.4730          | 0.8095   |
| 0.0011        | 40.0  | 1120 | 0.4760          | 0.7857   |
| 0.0011        | 41.0  | 1148 | 0.4762          | 0.7857   |
| 0.001         | 42.0  | 1176 | 0.4741          | 0.8095   |
| 0.0011        | 43.0  | 1204 | 0.4784          | 0.8095   |
| 0.001         | 44.0  | 1232 | 0.4806          | 0.7857   |
| 0.001         | 45.0  | 1260 | 0.4792          | 0.7857   |
| 0.001         | 46.0  | 1288 | 0.4801          | 0.7857   |
| 0.001         | 47.0  | 1316 | 0.4802          | 0.7857   |
| 0.0009        | 48.0  | 1344 | 0.4803          | 0.7857   |
| 0.001         | 49.0  | 1372 | 0.4803          | 0.7857   |
| 0.001         | 50.0  | 1400 | 0.4803          | 0.7857   |


### 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_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": 0.7857142857142857, "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