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# hushem_5x_deit_base_adamax_001_fold3

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: 4.0748
- Accuracy: 0.4651

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4157        | 1.0   | 28   | 1.4434          | 0.2558   |
| 1.3795        | 2.0   | 56   | 1.2758          | 0.4651   |
| 1.2039        | 3.0   | 84   | 1.4398          | 0.3256   |
| 1.2374        | 4.0   | 112  | 1.2828          | 0.3953   |
| 0.9763        | 5.0   | 140  | 1.0462          | 0.5814   |
| 0.9947        | 6.0   | 168  | 1.0570          | 0.5349   |
| 0.984         | 7.0   | 196  | 0.9874          | 0.6047   |
| 1.0476        | 8.0   | 224  | 1.1609          | 0.5581   |
| 0.8502        | 9.0   | 252  | 1.6864          | 0.5116   |
| 0.9652        | 10.0  | 280  | 0.9691          | 0.6512   |
| 1.0167        | 11.0  | 308  | 0.9040          | 0.6279   |
| 0.8838        | 12.0  | 336  | 1.0599          | 0.4884   |
| 0.8002        | 13.0  | 364  | 1.1020          | 0.3721   |
| 0.7509        | 14.0  | 392  | 0.8581          | 0.6744   |
| 0.7759        | 15.0  | 420  | 0.8348          | 0.6047   |
| 0.6809        | 16.0  | 448  | 0.8650          | 0.6279   |
| 0.6145        | 17.0  | 476  | 1.6492          | 0.3953   |
| 0.5427        | 18.0  | 504  | 1.4270          | 0.4419   |
| 0.5373        | 19.0  | 532  | 1.3497          | 0.4651   |
| 0.5816        | 20.0  | 560  | 1.2788          | 0.5116   |
| 0.5066        | 21.0  | 588  | 0.8857          | 0.6744   |
| 0.4263        | 22.0  | 616  | 1.0042          | 0.6744   |
| 0.4421        | 23.0  | 644  | 0.8870          | 0.7442   |
| 0.2947        | 24.0  | 672  | 1.5951          | 0.6279   |
| 0.3564        | 25.0  | 700  | 1.4096          | 0.5349   |
| 0.4309        | 26.0  | 728  | 1.5181          | 0.5116   |
| 0.2828        | 27.0  | 756  | 2.3004          | 0.3953   |
| 0.3386        | 28.0  | 784  | 2.1526          | 0.6047   |
| 0.1818        | 29.0  | 812  | 2.5940          | 0.5349   |
| 0.3444        | 30.0  | 840  | 2.3898          | 0.4884   |
| 0.2604        | 31.0  | 868  | 2.5996          | 0.5581   |
| 0.1135        | 32.0  | 896  | 2.5370          | 0.6047   |
| 0.1275        | 33.0  | 924  | 3.5621          | 0.5349   |
| 0.0534        | 34.0  | 952  | 3.3776          | 0.5116   |
| 0.0878        | 35.0  | 980  | 3.5763          | 0.5349   |
| 0.0297        | 36.0  | 1008 | 3.1205          | 0.5814   |
| 0.0316        | 37.0  | 1036 | 3.7999          | 0.5116   |
| 0.0083        | 38.0  | 1064 | 3.7418          | 0.5814   |
| 0.0256        | 39.0  | 1092 | 4.0409          | 0.5116   |
| 0.0017        | 40.0  | 1120 | 3.7639          | 0.4651   |
| 0.0016        | 41.0  | 1148 | 4.0848          | 0.4884   |
| 0.0008        | 42.0  | 1176 | 3.8952          | 0.4884   |
| 0.0002        | 43.0  | 1204 | 3.9086          | 0.4651   |
| 0.0002        | 44.0  | 1232 | 3.9976          | 0.4651   |
| 0.0001        | 45.0  | 1260 | 4.0424          | 0.4651   |
| 0.0001        | 46.0  | 1288 | 4.0591          | 0.4651   |
| 0.0001        | 47.0  | 1316 | 4.0703          | 0.4651   |
| 0.0001        | 48.0  | 1344 | 4.0747          | 0.4651   |
| 0.0001        | 49.0  | 1372 | 4.0748          | 0.4651   |
| 0.0001        | 50.0  | 1400 | 4.0748          | 0.4651   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.46511627906976744, "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