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# hushem_40x_beit_large_rmsprop_lr00001_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: 2.0835
- Accuracy: 0.8537

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0589        | 1.0   | 440   | 0.6985          | 0.9268   |
| 0.0016        | 2.0   | 880   | 0.7437          | 0.8537   |
| 0.0           | 3.0   | 1320  | 0.7702          | 0.8780   |
| 0.0           | 4.0   | 1760  | 0.1802          | 0.9268   |
| 0.0002        | 5.0   | 2200  | 0.7396          | 0.8049   |
| 0.0           | 6.0   | 2640  | 0.9543          | 0.8537   |
| 0.007         | 7.0   | 3080  | 1.4303          | 0.8537   |
| 0.0           | 8.0   | 3520  | 1.5477          | 0.8537   |
| 0.0           | 9.0   | 3960  | 1.3840          | 0.8049   |
| 0.0           | 10.0  | 4400  | 1.4402          | 0.8049   |
| 0.0           | 11.0  | 4840  | 1.1973          | 0.9024   |
| 0.0193        | 12.0  | 5280  | 2.4620          | 0.7805   |
| 0.0           | 13.0  | 5720  | 1.1346          | 0.8780   |
| 0.0           | 14.0  | 6160  | 0.7784          | 0.8293   |
| 0.0           | 15.0  | 6600  | 0.6545          | 0.8780   |
| 0.0           | 16.0  | 7040  | 1.2773          | 0.8293   |
| 0.0           | 17.0  | 7480  | 2.0528          | 0.7805   |
| 0.0           | 18.0  | 7920  | 0.2903          | 0.9756   |
| 0.0           | 19.0  | 8360  | 0.3449          | 0.9756   |
| 0.0           | 20.0  | 8800  | 0.6396          | 0.9512   |
| 0.0           | 21.0  | 9240  | 1.6472          | 0.8293   |
| 0.0           | 22.0  | 9680  | 1.4506          | 0.8293   |
| 0.0001        | 23.0  | 10120 | 0.7899          | 0.9268   |
| 0.0           | 24.0  | 10560 | 1.5290          | 0.8537   |
| 0.0           | 25.0  | 11000 | 1.2862          | 0.9024   |
| 0.0           | 26.0  | 11440 | 0.9347          | 0.9268   |
| 0.0           | 27.0  | 11880 | 0.9711          | 0.9268   |
| 0.0           | 28.0  | 12320 | 0.9987          | 0.9268   |
| 0.0           | 29.0  | 12760 | 0.8534          | 0.9268   |
| 0.0           | 30.0  | 13200 | 2.0736          | 0.8780   |
| 0.0           | 31.0  | 13640 | 2.0746          | 0.8780   |
| 0.0           | 32.0  | 14080 | 2.0277          | 0.8780   |
| 0.0           | 33.0  | 14520 | 2.0353          | 0.8780   |
| 0.0           | 34.0  | 14960 | 2.0241          | 0.8780   |
| 0.0           | 35.0  | 15400 | 2.0348          | 0.8537   |
| 0.0           | 36.0  | 15840 | 2.0783          | 0.8537   |
| 0.0           | 37.0  | 16280 | 2.0717          | 0.8537   |
| 0.0           | 38.0  | 16720 | 2.0771          | 0.8537   |
| 0.0           | 39.0  | 17160 | 2.0669          | 0.8537   |
| 0.0           | 40.0  | 17600 | 2.0633          | 0.8537   |
| 0.0           | 41.0  | 18040 | 2.0549          | 0.8537   |
| 0.0           | 42.0  | 18480 | 2.0704          | 0.8537   |
| 0.0           | 43.0  | 18920 | 2.0559          | 0.8537   |
| 0.0           | 44.0  | 19360 | 2.1610          | 0.8537   |
| 0.0           | 45.0  | 19800 | 2.1024          | 0.8537   |
| 0.0           | 46.0  | 20240 | 2.1021          | 0.8537   |
| 0.0           | 47.0  | 20680 | 2.1082          | 0.8537   |
| 0.0           | 48.0  | 21120 | 2.0842          | 0.8537   |
| 0.0           | 49.0  | 21560 | 2.0842          | 0.8537   |
| 0.0           | 50.0  | 22000 | 2.0835          | 0.8537   |


### 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_lr00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8536585365853658, "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