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# hushem_5x_deit_base_adamax_001_fold5

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: 2.0054
- Accuracy: 0.7317

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4493        | 1.0   | 28   | 1.4115          | 0.2439   |
| 1.4085        | 2.0   | 56   | 1.2905          | 0.2927   |
| 1.0193        | 3.0   | 84   | 1.4163          | 0.5366   |
| 1.1237        | 4.0   | 112  | 0.8304          | 0.6585   |
| 0.9964        | 5.0   | 140  | 0.7827          | 0.6585   |
| 0.9566        | 6.0   | 168  | 0.6329          | 0.7317   |
| 0.8689        | 7.0   | 196  | 0.6958          | 0.5854   |
| 0.8599        | 8.0   | 224  | 0.5797          | 0.7805   |
| 0.7599        | 9.0   | 252  | 0.9330          | 0.7805   |
| 0.7635        | 10.0  | 280  | 0.7011          | 0.6829   |
| 0.6603        | 11.0  | 308  | 0.9167          | 0.6829   |
| 0.7173        | 12.0  | 336  | 0.9009          | 0.5854   |
| 0.6949        | 13.0  | 364  | 0.5844          | 0.8049   |
| 0.5978        | 14.0  | 392  | 0.9237          | 0.7805   |
| 0.6548        | 15.0  | 420  | 0.5173          | 0.8049   |
| 0.5794        | 16.0  | 448  | 0.9750          | 0.7073   |
| 0.5927        | 17.0  | 476  | 0.8636          | 0.8049   |
| 0.4408        | 18.0  | 504  | 0.5076          | 0.8537   |
| 0.5047        | 19.0  | 532  | 0.9978          | 0.7073   |
| 0.5155        | 20.0  | 560  | 0.8993          | 0.7805   |
| 0.3022        | 21.0  | 588  | 1.0654          | 0.7805   |
| 0.3634        | 22.0  | 616  | 1.0189          | 0.8049   |
| 0.3346        | 23.0  | 644  | 0.9586          | 0.7805   |
| 0.2995        | 24.0  | 672  | 0.9302          | 0.7317   |
| 0.345         | 25.0  | 700  | 1.2111          | 0.7561   |
| 0.2746        | 26.0  | 728  | 1.7821          | 0.6585   |
| 0.1747        | 27.0  | 756  | 2.2030          | 0.6585   |
| 0.214         | 28.0  | 784  | 1.2078          | 0.6585   |
| 0.0609        | 29.0  | 812  | 1.3388          | 0.8049   |
| 0.0765        | 30.0  | 840  | 1.4109          | 0.7561   |
| 0.0654        | 31.0  | 868  | 1.4789          | 0.7561   |
| 0.0843        | 32.0  | 896  | 1.4884          | 0.7073   |
| 0.0165        | 33.0  | 924  | 2.0871          | 0.6341   |
| 0.0138        | 34.0  | 952  | 2.0174          | 0.6341   |
| 0.0253        | 35.0  | 980  | 2.0599          | 0.6098   |
| 0.0093        | 36.0  | 1008 | 1.7213          | 0.7317   |
| 0.0034        | 37.0  | 1036 | 1.8852          | 0.7561   |
| 0.0001        | 38.0  | 1064 | 1.8415          | 0.7561   |
| 0.0014        | 39.0  | 1092 | 1.8486          | 0.7073   |
| 0.001         | 40.0  | 1120 | 1.8899          | 0.7561   |
| 0.0001        | 41.0  | 1148 | 1.9569          | 0.7317   |
| 0.0001        | 42.0  | 1176 | 1.9763          | 0.7317   |
| 0.0001        | 43.0  | 1204 | 1.9852          | 0.7317   |
| 0.0001        | 44.0  | 1232 | 1.9927          | 0.7317   |
| 0.0001        | 45.0  | 1260 | 1.9966          | 0.7317   |
| 0.0           | 46.0  | 1288 | 2.0017          | 0.7317   |
| 0.0           | 47.0  | 1316 | 2.0041          | 0.7317   |
| 0.0001        | 48.0  | 1344 | 2.0053          | 0.7317   |
| 0.0           | 49.0  | 1372 | 2.0054          | 0.7317   |
| 0.0           | 50.0  | 1400 | 2.0054          | 0.7317   |


### 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_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7317073170731707, "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