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# hushem_5x_deit_base_adamax_001_fold4

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8006
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4494        | 1.0   | 28   | 1.3719          | 0.2619   |
| 1.2522        | 2.0   | 56   | 0.9742          | 0.6667   |
| 1.0638        | 3.0   | 84   | 0.9282          | 0.4286   |
| 0.9326        | 4.0   | 112  | 0.9751          | 0.7381   |
| 0.9775        | 5.0   | 140  | 0.6128          | 0.8333   |
| 0.8386        | 6.0   | 168  | 0.6453          | 0.6905   |
| 0.7523        | 7.0   | 196  | 0.8760          | 0.5952   |
| 0.8483        | 8.0   | 224  | 0.6776          | 0.6905   |
| 0.7007        | 9.0   | 252  | 0.6406          | 0.7381   |
| 0.6736        | 10.0  | 280  | 1.1732          | 0.5714   |
| 0.6667        | 11.0  | 308  | 0.8999          | 0.7143   |
| 0.5535        | 12.0  | 336  | 0.7518          | 0.7143   |
| 0.5519        | 13.0  | 364  | 1.2198          | 0.6429   |
| 0.4746        | 14.0  | 392  | 1.2629          | 0.6190   |
| 0.4049        | 15.0  | 420  | 1.0670          | 0.7143   |
| 0.2485        | 16.0  | 448  | 1.3207          | 0.6667   |
| 0.2835        | 17.0  | 476  | 0.9080          | 0.7143   |
| 0.1908        | 18.0  | 504  | 0.9684          | 0.6905   |
| 0.1239        | 19.0  | 532  | 0.8600          | 0.8333   |
| 0.2177        | 20.0  | 560  | 1.2908          | 0.6667   |
| 0.0633        | 21.0  | 588  | 1.7014          | 0.7143   |
| 0.0847        | 22.0  | 616  | 1.3740          | 0.7857   |
| 0.1199        | 23.0  | 644  | 1.1620          | 0.8095   |
| 0.0618        | 24.0  | 672  | 1.7626          | 0.7857   |
| 0.0552        | 25.0  | 700  | 1.7596          | 0.7381   |
| 0.0166        | 26.0  | 728  | 1.4380          | 0.7143   |
| 0.0048        | 27.0  | 756  | 2.1450          | 0.6667   |
| 0.0064        | 28.0  | 784  | 1.7983          | 0.7381   |
| 0.0065        | 29.0  | 812  | 1.9453          | 0.6429   |
| 0.0052        | 30.0  | 840  | 1.5896          | 0.7619   |
| 0.0125        | 31.0  | 868  | 1.6540          | 0.7381   |
| 0.0008        | 32.0  | 896  | 1.7879          | 0.7619   |
| 0.0001        | 33.0  | 924  | 1.9506          | 0.7381   |
| 0.0002        | 34.0  | 952  | 1.7166          | 0.7143   |
| 0.0           | 35.0  | 980  | 1.7316          | 0.6905   |
| 0.0           | 36.0  | 1008 | 1.7446          | 0.6905   |
| 0.0           | 37.0  | 1036 | 1.7559          | 0.6905   |
| 0.0           | 38.0  | 1064 | 1.7638          | 0.6905   |
| 0.0           | 39.0  | 1092 | 1.7724          | 0.6905   |
| 0.0           | 40.0  | 1120 | 1.7784          | 0.6905   |
| 0.0           | 41.0  | 1148 | 1.7832          | 0.6905   |
| 0.0           | 42.0  | 1176 | 1.7877          | 0.6905   |
| 0.0           | 43.0  | 1204 | 1.7918          | 0.6905   |
| 0.0           | 44.0  | 1232 | 1.7950          | 0.6905   |
| 0.0           | 45.0  | 1260 | 1.7970          | 0.6905   |
| 0.0           | 46.0  | 1288 | 1.7988          | 0.6905   |
| 0.0           | 47.0  | 1316 | 1.8001          | 0.6905   |
| 0.0           | 48.0  | 1344 | 1.8006          | 0.6905   |
| 0.0           | 49.0  | 1372 | 1.8006          | 0.6905   |
| 0.0           | 50.0  | 1400 | 1.8006          | 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-base-patch16-224", "model-index": [{"name": "hushem_5x_deit_base_adamax_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-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us