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# hushem_5x_beit_base_adamax_00001_fold4

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: 0.2768
- Accuracy: 0.9286

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2143        | 1.0   | 28   | 1.1034          | 0.5714   |
| 0.7775        | 2.0   | 56   | 0.7868          | 0.7143   |
| 0.4533        | 3.0   | 84   | 0.5700          | 0.8571   |
| 0.3037        | 4.0   | 112  | 0.4325          | 0.9048   |
| 0.1612        | 5.0   | 140  | 0.3176          | 0.9524   |
| 0.1058        | 6.0   | 168  | 0.2780          | 0.9524   |
| 0.0913        | 7.0   | 196  | 0.2215          | 0.9524   |
| 0.0514        | 8.0   | 224  | 0.1972          | 0.9524   |
| 0.0348        | 9.0   | 252  | 0.1996          | 0.9524   |
| 0.0351        | 10.0  | 280  | 0.1992          | 0.9524   |
| 0.0183        | 11.0  | 308  | 0.2116          | 0.9286   |
| 0.0237        | 12.0  | 336  | 0.2277          | 0.9286   |
| 0.0106        | 13.0  | 364  | 0.2270          | 0.9286   |
| 0.0108        | 14.0  | 392  | 0.2101          | 0.9524   |
| 0.0149        | 15.0  | 420  | 0.2231          | 0.9524   |
| 0.0076        | 16.0  | 448  | 0.2350          | 0.9048   |
| 0.0086        | 17.0  | 476  | 0.2204          | 0.9286   |
| 0.0033        | 18.0  | 504  | 0.2707          | 0.9286   |
| 0.0048        | 19.0  | 532  | 0.2227          | 0.9286   |
| 0.0041        | 20.0  | 560  | 0.2590          | 0.9286   |
| 0.0023        | 21.0  | 588  | 0.2904          | 0.9048   |
| 0.0045        | 22.0  | 616  | 0.2887          | 0.9286   |
| 0.0027        | 23.0  | 644  | 0.2955          | 0.9286   |
| 0.0033        | 24.0  | 672  | 0.2912          | 0.9286   |
| 0.0028        | 25.0  | 700  | 0.2636          | 0.9286   |
| 0.0018        | 26.0  | 728  | 0.2618          | 0.9286   |
| 0.0028        | 27.0  | 756  | 0.2893          | 0.9286   |
| 0.0019        | 28.0  | 784  | 0.2937          | 0.9286   |
| 0.0014        | 29.0  | 812  | 0.2912          | 0.9048   |
| 0.0031        | 30.0  | 840  | 0.2819          | 0.9048   |
| 0.0013        | 31.0  | 868  | 0.2819          | 0.9524   |
| 0.006         | 32.0  | 896  | 0.2996          | 0.9286   |
| 0.001         | 33.0  | 924  | 0.2836          | 0.9048   |
| 0.0011        | 34.0  | 952  | 0.2841          | 0.9286   |
| 0.0015        | 35.0  | 980  | 0.2638          | 0.9286   |
| 0.0022        | 36.0  | 1008 | 0.2845          | 0.9286   |
| 0.001         | 37.0  | 1036 | 0.2920          | 0.9286   |
| 0.0015        | 38.0  | 1064 | 0.2827          | 0.9286   |
| 0.0029        | 39.0  | 1092 | 0.2797          | 0.9286   |
| 0.002         | 40.0  | 1120 | 0.2954          | 0.9286   |
| 0.0017        | 41.0  | 1148 | 0.3039          | 0.9286   |
| 0.001         | 42.0  | 1176 | 0.3143          | 0.9286   |
| 0.0014        | 43.0  | 1204 | 0.3005          | 0.9286   |
| 0.0014        | 44.0  | 1232 | 0.2937          | 0.9286   |
| 0.0019        | 45.0  | 1260 | 0.2833          | 0.9286   |
| 0.0042        | 46.0  | 1288 | 0.2805          | 0.9286   |
| 0.0013        | 47.0  | 1316 | 0.2768          | 0.9286   |
| 0.0008        | 48.0  | 1344 | 0.2768          | 0.9286   |
| 0.0031        | 49.0  | 1372 | 0.2768          | 0.9286   |
| 0.0013        | 50.0  | 1400 | 0.2768          | 0.9286   |


### 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_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": 0.9285714285714286, "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