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# hushem_5x_beit_base_adamax_001_fold3

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7065
- Accuracy: 0.6977

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4764        | 1.0   | 28   | 1.3308          | 0.4651   |
| 1.3399        | 2.0   | 56   | 1.2727          | 0.5116   |
| 1.2309        | 3.0   | 84   | 1.0539          | 0.5349   |
| 1.0517        | 4.0   | 112  | 1.0384          | 0.6279   |
| 0.9736        | 5.0   | 140  | 1.1313          | 0.5349   |
| 1.0108        | 6.0   | 168  | 0.6569          | 0.8140   |
| 0.9287        | 7.0   | 196  | 0.7779          | 0.7674   |
| 0.9063        | 8.0   | 224  | 0.8802          | 0.5581   |
| 0.7994        | 9.0   | 252  | 1.1244          | 0.5581   |
| 0.8319        | 10.0  | 280  | 0.7284          | 0.7209   |
| 0.8096        | 11.0  | 308  | 0.7775          | 0.7209   |
| 0.8274        | 12.0  | 336  | 0.7683          | 0.6744   |
| 0.798         | 13.0  | 364  | 0.8219          | 0.6512   |
| 0.6756        | 14.0  | 392  | 0.5656          | 0.7442   |
| 0.9098        | 15.0  | 420  | 0.6922          | 0.6279   |
| 0.6261        | 16.0  | 448  | 1.0949          | 0.5814   |
| 0.6243        | 17.0  | 476  | 0.7154          | 0.7209   |
| 0.7247        | 18.0  | 504  | 0.6429          | 0.7674   |
| 0.6106        | 19.0  | 532  | 0.7927          | 0.6744   |
| 0.4831        | 20.0  | 560  | 0.6060          | 0.7674   |
| 0.5359        | 21.0  | 588  | 1.2593          | 0.5349   |
| 0.429         | 22.0  | 616  | 1.0232          | 0.6744   |
| 0.4536        | 23.0  | 644  | 1.2564          | 0.6744   |
| 0.2969        | 24.0  | 672  | 1.2153          | 0.6279   |
| 0.3018        | 25.0  | 700  | 1.3650          | 0.5814   |
| 0.2695        | 26.0  | 728  | 1.6759          | 0.6279   |
| 0.2235        | 27.0  | 756  | 1.8158          | 0.5814   |
| 0.2674        | 28.0  | 784  | 1.7475          | 0.6977   |
| 0.1711        | 29.0  | 812  | 1.5630          | 0.7209   |
| 0.1241        | 30.0  | 840  | 1.5976          | 0.7442   |
| 0.1378        | 31.0  | 868  | 1.8498          | 0.7209   |
| 0.1016        | 32.0  | 896  | 2.3022          | 0.6279   |
| 0.1245        | 33.0  | 924  | 2.0178          | 0.6047   |
| 0.1029        | 34.0  | 952  | 2.0725          | 0.6744   |
| 0.0329        | 35.0  | 980  | 1.6046          | 0.7674   |
| 0.1038        | 36.0  | 1008 | 2.3364          | 0.6047   |
| 0.055         | 37.0  | 1036 | 3.1044          | 0.5581   |
| 0.0031        | 38.0  | 1064 | 2.6896          | 0.6512   |
| 0.0537        | 39.0  | 1092 | 3.2350          | 0.6047   |
| 0.0484        | 40.0  | 1120 | 3.5002          | 0.5814   |
| 0.0311        | 41.0  | 1148 | 3.0948          | 0.6512   |
| 0.0491        | 42.0  | 1176 | 2.8268          | 0.6977   |
| 0.0023        | 43.0  | 1204 | 2.5306          | 0.6977   |
| 0.0192        | 44.0  | 1232 | 2.3977          | 0.6977   |
| 0.0339        | 45.0  | 1260 | 2.5488          | 0.6977   |
| 0.0369        | 46.0  | 1288 | 2.5878          | 0.7209   |
| 0.049         | 47.0  | 1316 | 2.7159          | 0.6977   |
| 0.0044        | 48.0  | 1344 | 2.7074          | 0.6977   |
| 0.0183        | 49.0  | 1372 | 2.7065          | 0.6977   |
| 0.0409        | 50.0  | 1400 | 2.7065          | 0.6977   |


### 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": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_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": 0.6976744186046512, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us