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# hushem_5x_beit_base_sgd_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: 1.4856
- Accuracy: 0.3095

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5648        | 1.0   | 28   | 1.5024          | 0.3095   |
| 1.5958        | 2.0   | 56   | 1.5016          | 0.3095   |
| 1.5478        | 3.0   | 84   | 1.5008          | 0.3095   |
| 1.6175        | 4.0   | 112  | 1.5001          | 0.3095   |
| 1.5019        | 5.0   | 140  | 1.4994          | 0.3095   |
| 1.5612        | 6.0   | 168  | 1.4987          | 0.3095   |
| 1.5556        | 7.0   | 196  | 1.4981          | 0.3095   |
| 1.5275        | 8.0   | 224  | 1.4974          | 0.3095   |
| 1.529         | 9.0   | 252  | 1.4968          | 0.3095   |
| 1.5306        | 10.0  | 280  | 1.4962          | 0.3095   |
| 1.5486        | 11.0  | 308  | 1.4956          | 0.3095   |
| 1.5567        | 12.0  | 336  | 1.4950          | 0.3095   |
| 1.5578        | 13.0  | 364  | 1.4945          | 0.3095   |
| 1.5601        | 14.0  | 392  | 1.4939          | 0.3095   |
| 1.5869        | 15.0  | 420  | 1.4934          | 0.3095   |
| 1.5292        | 16.0  | 448  | 1.4929          | 0.3095   |
| 1.584         | 17.0  | 476  | 1.4924          | 0.3095   |
| 1.5709        | 18.0  | 504  | 1.4919          | 0.3095   |
| 1.5246        | 19.0  | 532  | 1.4915          | 0.3095   |
| 1.508         | 20.0  | 560  | 1.4911          | 0.3095   |
| 1.5627        | 21.0  | 588  | 1.4907          | 0.3095   |
| 1.543         | 22.0  | 616  | 1.4904          | 0.3095   |
| 1.5306        | 23.0  | 644  | 1.4900          | 0.3095   |
| 1.5347        | 24.0  | 672  | 1.4896          | 0.3095   |
| 1.5296        | 25.0  | 700  | 1.4893          | 0.3095   |
| 1.5722        | 26.0  | 728  | 1.4889          | 0.3095   |
| 1.6103        | 27.0  | 756  | 1.4886          | 0.3095   |
| 1.5352        | 28.0  | 784  | 1.4883          | 0.3095   |
| 1.5133        | 29.0  | 812  | 1.4880          | 0.3095   |
| 1.4677        | 30.0  | 840  | 1.4878          | 0.3095   |
| 1.5424        | 31.0  | 868  | 1.4876          | 0.3095   |
| 1.5132        | 32.0  | 896  | 1.4873          | 0.3095   |
| 1.5611        | 33.0  | 924  | 1.4871          | 0.3095   |
| 1.5494        | 34.0  | 952  | 1.4869          | 0.3095   |
| 1.5087        | 35.0  | 980  | 1.4867          | 0.3095   |
| 1.5719        | 36.0  | 1008 | 1.4865          | 0.3095   |
| 1.5037        | 37.0  | 1036 | 1.4864          | 0.3095   |
| 1.5457        | 38.0  | 1064 | 1.4863          | 0.3095   |
| 1.5227        | 39.0  | 1092 | 1.4861          | 0.3095   |
| 1.5024        | 40.0  | 1120 | 1.4860          | 0.3095   |
| 1.5112        | 41.0  | 1148 | 1.4859          | 0.3095   |
| 1.4872        | 42.0  | 1176 | 1.4858          | 0.3095   |
| 1.5623        | 43.0  | 1204 | 1.4858          | 0.3095   |
| 1.5147        | 44.0  | 1232 | 1.4857          | 0.3095   |
| 1.5196        | 45.0  | 1260 | 1.4857          | 0.3095   |
| 1.5574        | 46.0  | 1288 | 1.4856          | 0.3095   |
| 1.5277        | 47.0  | 1316 | 1.4856          | 0.3095   |
| 1.602         | 48.0  | 1344 | 1.4856          | 0.3095   |
| 1.5259        | 49.0  | 1372 | 1.4856          | 0.3095   |
| 1.5075        | 50.0  | 1400 | 1.4856          | 0.3095   |


### 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_sgd_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": 0.30952380952380953, "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