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# hushem_5x_beit_base_adamax_00001_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: 0.4974
- Accuracy: 0.9070

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2118        | 1.0   | 28   | 1.1325          | 0.6047   |
| 0.7198        | 2.0   | 56   | 0.8388          | 0.6744   |
| 0.3881        | 3.0   | 84   | 0.6224          | 0.7674   |
| 0.2597        | 4.0   | 112  | 0.4679          | 0.8140   |
| 0.1551        | 5.0   | 140  | 0.4682          | 0.8140   |
| 0.1015        | 6.0   | 168  | 0.3870          | 0.8372   |
| 0.0767        | 7.0   | 196  | 0.3615          | 0.8837   |
| 0.0522        | 8.0   | 224  | 0.3630          | 0.8837   |
| 0.0344        | 9.0   | 252  | 0.4112          | 0.8837   |
| 0.0303        | 10.0  | 280  | 0.4026          | 0.8837   |
| 0.0199        | 11.0  | 308  | 0.3842          | 0.9070   |
| 0.0106        | 12.0  | 336  | 0.3943          | 0.8605   |
| 0.0205        | 13.0  | 364  | 0.3879          | 0.9070   |
| 0.008         | 14.0  | 392  | 0.3444          | 0.8837   |
| 0.0066        | 15.0  | 420  | 0.3829          | 0.9070   |
| 0.0068        | 16.0  | 448  | 0.4064          | 0.8837   |
| 0.0104        | 17.0  | 476  | 0.3534          | 0.9302   |
| 0.0048        | 18.0  | 504  | 0.3744          | 0.9070   |
| 0.0062        | 19.0  | 532  | 0.4146          | 0.9070   |
| 0.0025        | 20.0  | 560  | 0.3803          | 0.9070   |
| 0.0032        | 21.0  | 588  | 0.4244          | 0.9070   |
| 0.0031        | 22.0  | 616  | 0.4663          | 0.9070   |
| 0.0021        | 23.0  | 644  | 0.4157          | 0.9070   |
| 0.0026        | 24.0  | 672  | 0.4816          | 0.9070   |
| 0.0013        | 25.0  | 700  | 0.4216          | 0.9070   |
| 0.0017        | 26.0  | 728  | 0.4591          | 0.9070   |
| 0.0021        | 27.0  | 756  | 0.4515          | 0.9070   |
| 0.0024        | 28.0  | 784  | 0.4442          | 0.8837   |
| 0.0026        | 29.0  | 812  | 0.4504          | 0.9070   |
| 0.0009        | 30.0  | 840  | 0.4703          | 0.9070   |
| 0.0047        | 31.0  | 868  | 0.4689          | 0.9070   |
| 0.0067        | 32.0  | 896  | 0.4798          | 0.9070   |
| 0.0009        | 33.0  | 924  | 0.5058          | 0.9070   |
| 0.0013        | 34.0  | 952  | 0.4786          | 0.9070   |
| 0.0022        | 35.0  | 980  | 0.4689          | 0.9070   |
| 0.009         | 36.0  | 1008 | 0.4633          | 0.9070   |
| 0.0009        | 37.0  | 1036 | 0.4823          | 0.9070   |
| 0.0013        | 38.0  | 1064 | 0.4868          | 0.9070   |
| 0.0024        | 39.0  | 1092 | 0.5030          | 0.9070   |
| 0.004         | 40.0  | 1120 | 0.4969          | 0.9070   |
| 0.0014        | 41.0  | 1148 | 0.4951          | 0.9070   |
| 0.0017        | 42.0  | 1176 | 0.4894          | 0.9070   |
| 0.0014        | 43.0  | 1204 | 0.4881          | 0.9070   |
| 0.0013        | 44.0  | 1232 | 0.4878          | 0.9070   |
| 0.0022        | 45.0  | 1260 | 0.4914          | 0.9070   |
| 0.0023        | 46.0  | 1288 | 0.4962          | 0.9070   |
| 0.0015        | 47.0  | 1316 | 0.4961          | 0.9070   |
| 0.0017        | 48.0  | 1344 | 0.4974          | 0.9070   |
| 0.0007        | 49.0  | 1372 | 0.4974          | 0.9070   |
| 0.0006        | 50.0  | 1400 | 0.4974          | 0.9070   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9069767441860465, "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