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# hushem_5x_beit_base_adamax_001_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: 2.1895
- Accuracy: 0.7381

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.398         | 1.0   | 28   | 1.3161          | 0.2619   |
| 1.3348        | 2.0   | 56   | 1.1486          | 0.5      |
| 1.2598        | 3.0   | 84   | 1.2723          | 0.4762   |
| 1.0258        | 4.0   | 112  | 2.5380          | 0.3571   |
| 0.9514        | 5.0   | 140  | 0.7752          | 0.6667   |
| 0.9022        | 6.0   | 168  | 0.7061          | 0.7381   |
| 0.894         | 7.0   | 196  | 0.9563          | 0.6190   |
| 0.9803        | 8.0   | 224  | 0.6994          | 0.7381   |
| 0.8819        | 9.0   | 252  | 0.6742          | 0.7619   |
| 0.8414        | 10.0  | 280  | 0.7881          | 0.6667   |
| 0.8005        | 11.0  | 308  | 0.9825          | 0.7143   |
| 0.8103        | 12.0  | 336  | 0.6127          | 0.7619   |
| 0.8302        | 13.0  | 364  | 0.8926          | 0.7143   |
| 0.7477        | 14.0  | 392  | 0.8951          | 0.6190   |
| 0.7772        | 15.0  | 420  | 0.6142          | 0.7619   |
| 0.6718        | 16.0  | 448  | 0.6386          | 0.7619   |
| 0.6971        | 17.0  | 476  | 0.8030          | 0.6429   |
| 0.6705        | 18.0  | 504  | 0.8028          | 0.6667   |
| 0.6156        | 19.0  | 532  | 0.8667          | 0.6429   |
| 0.4804        | 20.0  | 560  | 0.6053          | 0.7381   |
| 0.3939        | 21.0  | 588  | 0.8598          | 0.7381   |
| 0.485         | 22.0  | 616  | 0.7061          | 0.7381   |
| 0.4778        | 23.0  | 644  | 1.0522          | 0.6190   |
| 0.4222        | 24.0  | 672  | 0.8683          | 0.7381   |
| 0.2892        | 25.0  | 700  | 1.0772          | 0.7143   |
| 0.3633        | 26.0  | 728  | 0.8242          | 0.7857   |
| 0.4528        | 27.0  | 756  | 1.4370          | 0.6667   |
| 0.2621        | 28.0  | 784  | 1.0095          | 0.8095   |
| 0.1921        | 29.0  | 812  | 1.3782          | 0.7143   |
| 0.1811        | 30.0  | 840  | 1.8693          | 0.7143   |
| 0.1481        | 31.0  | 868  | 1.8742          | 0.7619   |
| 0.1394        | 32.0  | 896  | 1.7130          | 0.7143   |
| 0.0623        | 33.0  | 924  | 1.6326          | 0.7619   |
| 0.1726        | 34.0  | 952  | 1.5273          | 0.7381   |
| 0.1641        | 35.0  | 980  | 1.3046          | 0.8333   |
| 0.0573        | 36.0  | 1008 | 2.1424          | 0.6667   |
| 0.0574        | 37.0  | 1036 | 2.1687          | 0.7143   |
| 0.0558        | 38.0  | 1064 | 1.6907          | 0.7619   |
| 0.0165        | 39.0  | 1092 | 2.0112          | 0.7619   |
| 0.052         | 40.0  | 1120 | 1.7998          | 0.7619   |
| 0.0524        | 41.0  | 1148 | 2.3373          | 0.7143   |
| 0.0976        | 42.0  | 1176 | 2.2060          | 0.7381   |
| 0.0064        | 43.0  | 1204 | 2.2711          | 0.7619   |
| 0.0205        | 44.0  | 1232 | 2.4091          | 0.7619   |
| 0.0254        | 45.0  | 1260 | 2.3470          | 0.7381   |
| 0.0473        | 46.0  | 1288 | 2.3652          | 0.7381   |
| 0.0464        | 47.0  | 1316 | 2.2959          | 0.7381   |
| 0.0006        | 48.0  | 1344 | 2.1947          | 0.7381   |
| 0.0143        | 49.0  | 1372 | 2.1895          | 0.7381   |
| 0.0223        | 50.0  | 1400 | 2.1895          | 0.7381   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7380952380952381, "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