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# hushem_40x_beit_large_rmsprop_lr001_fold4

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: 2.8764
- Accuracy: 0.8095

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.164         | 1.0   | 437   | 0.8444          | 0.5952   |
| 0.9201        | 2.0   | 874   | 0.6246          | 0.8095   |
| 0.7767        | 3.0   | 1311  | 0.6984          | 0.6905   |
| 0.6918        | 4.0   | 1748  | 0.6058          | 0.7619   |
| 0.6739        | 5.0   | 2185  | 0.7140          | 0.6905   |
| 0.5663        | 6.0   | 2622  | 0.5719          | 0.7619   |
| 0.5208        | 7.0   | 3059  | 0.9175          | 0.6667   |
| 0.6419        | 8.0   | 3496  | 0.5632          | 0.8095   |
| 0.4562        | 9.0   | 3933  | 0.6111          | 0.7143   |
| 0.4296        | 10.0  | 4370  | 0.8112          | 0.7381   |
| 0.4275        | 11.0  | 4807  | 0.4742          | 0.8095   |
| 0.3111        | 12.0  | 5244  | 1.0447          | 0.6905   |
| 0.2921        | 13.0  | 5681  | 0.7018          | 0.8571   |
| 0.3062        | 14.0  | 6118  | 0.7131          | 0.7857   |
| 0.2601        | 15.0  | 6555  | 0.6180          | 0.8095   |
| 0.061         | 16.0  | 6992  | 0.7227          | 0.8810   |
| 0.191         | 17.0  | 7429  | 0.9603          | 0.8095   |
| 0.0921        | 18.0  | 7866  | 0.6795          | 0.8333   |
| 0.0603        | 19.0  | 8303  | 1.6222          | 0.7143   |
| 0.0709        | 20.0  | 8740  | 1.2106          | 0.7381   |
| 0.0997        | 21.0  | 9177  | 0.7170          | 0.8571   |
| 0.0625        | 22.0  | 9614  | 1.5687          | 0.8333   |
| 0.0299        | 23.0  | 10051 | 0.9945          | 0.8333   |
| 0.0938        | 24.0  | 10488 | 1.2049          | 0.8333   |
| 0.0067        | 25.0  | 10925 | 1.1187          | 0.8333   |
| 0.0008        | 26.0  | 11362 | 1.0477          | 0.8095   |
| 0.0356        | 27.0  | 11799 | 2.2409          | 0.7381   |
| 0.0186        | 28.0  | 12236 | 1.9341          | 0.7857   |
| 0.025         | 29.0  | 12673 | 1.8504          | 0.7381   |
| 0.0116        | 30.0  | 13110 | 1.4267          | 0.7619   |
| 0.0541        | 31.0  | 13547 | 1.5435          | 0.7857   |
| 0.0005        | 32.0  | 13984 | 1.7018          | 0.8095   |
| 0.0002        | 33.0  | 14421 | 1.6369          | 0.7619   |
| 0.0002        | 34.0  | 14858 | 1.8314          | 0.8333   |
| 0.0           | 35.0  | 15295 | 2.4737          | 0.7381   |
| 0.0119        | 36.0  | 15732 | 1.8045          | 0.8095   |
| 0.0           | 37.0  | 16169 | 2.1299          | 0.8095   |
| 0.0006        | 38.0  | 16606 | 1.9376          | 0.8571   |
| 0.0           | 39.0  | 17043 | 2.1673          | 0.7857   |
| 0.0007        | 40.0  | 17480 | 1.5289          | 0.8333   |
| 0.0014        | 41.0  | 17917 | 3.1811          | 0.7381   |
| 0.0           | 42.0  | 18354 | 2.8927          | 0.7619   |
| 0.0003        | 43.0  | 18791 | 4.2462          | 0.6667   |
| 0.0           | 44.0  | 19228 | 2.7205          | 0.7857   |
| 0.0002        | 45.0  | 19665 | 3.0699          | 0.7619   |
| 0.0           | 46.0  | 20102 | 3.3164          | 0.7619   |
| 0.0           | 47.0  | 20539 | 2.6033          | 0.8333   |
| 0.0           | 48.0  | 20976 | 2.6538          | 0.8571   |
| 0.0           | 49.0  | 21413 | 2.8111          | 0.8571   |
| 0.0           | 50.0  | 21850 | 2.8764          | 0.8095   |


### 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_rmsprop_lr001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8095238095238095, "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