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# hushem_40x_beit_large_sgd_lr001_fold5

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3799
- Accuracy: 0.9268

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9789        | 1.0   | 440   | 1.0424          | 0.5610   |
| 0.7478        | 2.0   | 880   | 0.6965          | 0.8293   |
| 0.5191        | 3.0   | 1320  | 0.5165          | 0.8537   |
| 0.3115        | 4.0   | 1760  | 0.4213          | 0.8537   |
| 0.3236        | 5.0   | 2200  | 0.3995          | 0.8780   |
| 0.2688        | 6.0   | 2640  | 0.3111          | 0.8780   |
| 0.155         | 7.0   | 3080  | 0.2864          | 0.9024   |
| 0.1461        | 8.0   | 3520  | 0.3077          | 0.8780   |
| 0.1162        | 9.0   | 3960  | 0.3004          | 0.8780   |
| 0.0981        | 10.0  | 4400  | 0.3203          | 0.8780   |
| 0.058         | 11.0  | 4840  | 0.3078          | 0.8780   |
| 0.1022        | 12.0  | 5280  | 0.3454          | 0.8780   |
| 0.0477        | 13.0  | 5720  | 0.3257          | 0.9024   |
| 0.0569        | 14.0  | 6160  | 0.3149          | 0.9024   |
| 0.0554        | 15.0  | 6600  | 0.3109          | 0.9024   |
| 0.0453        | 16.0  | 7040  | 0.3212          | 0.9024   |
| 0.0356        | 17.0  | 7480  | 0.3296          | 0.9024   |
| 0.0201        | 18.0  | 7920  | 0.3148          | 0.9024   |
| 0.0169        | 19.0  | 8360  | 0.3347          | 0.9024   |
| 0.0206        | 20.0  | 8800  | 0.3421          | 0.9024   |
| 0.0283        | 21.0  | 9240  | 0.3487          | 0.9024   |
| 0.0143        | 22.0  | 9680  | 0.3486          | 0.9024   |
| 0.0171        | 23.0  | 10120 | 0.3386          | 0.9268   |
| 0.0139        | 24.0  | 10560 | 0.3383          | 0.9024   |
| 0.0104        | 25.0  | 11000 | 0.3149          | 0.9268   |
| 0.0123        | 26.0  | 11440 | 0.3573          | 0.9024   |
| 0.0083        | 27.0  | 11880 | 0.3535          | 0.9024   |
| 0.0276        | 28.0  | 12320 | 0.3562          | 0.9024   |
| 0.023         | 29.0  | 12760 | 0.3301          | 0.9268   |
| 0.004         | 30.0  | 13200 | 0.3420          | 0.9268   |
| 0.0033        | 31.0  | 13640 | 0.3664          | 0.9024   |
| 0.0118        | 32.0  | 14080 | 0.3664          | 0.9268   |
| 0.0048        | 33.0  | 14520 | 0.3517          | 0.9268   |
| 0.0107        | 34.0  | 14960 | 0.3703          | 0.9268   |
| 0.0018        | 35.0  | 15400 | 0.3666          | 0.9268   |
| 0.0112        | 36.0  | 15840 | 0.3772          | 0.9268   |
| 0.0038        | 37.0  | 16280 | 0.3677          | 0.9268   |
| 0.0579        | 38.0  | 16720 | 0.3696          | 0.9268   |
| 0.0042        | 39.0  | 17160 | 0.3607          | 0.9268   |
| 0.006         | 40.0  | 17600 | 0.3742          | 0.9268   |
| 0.0054        | 41.0  | 18040 | 0.3727          | 0.9268   |
| 0.0034        | 42.0  | 18480 | 0.3702          | 0.9268   |
| 0.0047        | 43.0  | 18920 | 0.3690          | 0.9268   |
| 0.0164        | 44.0  | 19360 | 0.3769          | 0.9268   |
| 0.0035        | 45.0  | 19800 | 0.3787          | 0.9268   |
| 0.0171        | 46.0  | 20240 | 0.3824          | 0.9268   |
| 0.0022        | 47.0  | 20680 | 0.3819          | 0.9268   |
| 0.0142        | 48.0  | 21120 | 0.3781          | 0.9268   |
| 0.0009        | 49.0  | 21560 | 0.3790          | 0.9268   |
| 0.0039        | 50.0  | 22000 | 0.3799          | 0.9268   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "hushem_40x_beit_large_sgd_lr001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.926829268292683, "name": "Accuracy"}]}]}]}
transformers safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us