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# hushem_40x_beit_large_rmsprop_lr0001_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: 2.7065
- Accuracy: 0.7805

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6898        | 1.0   | 440   | 0.7113          | 0.7073   |
| 0.4369        | 2.0   | 880   | 0.6242          | 0.7561   |
| 0.5546        | 3.0   | 1320  | 1.1688          | 0.6341   |
| 0.2984        | 4.0   | 1760  | 2.1250          | 0.5122   |
| 0.1343        | 5.0   | 2200  | 1.1792          | 0.7561   |
| 0.1571        | 6.0   | 2640  | 1.0541          | 0.7805   |
| 0.2023        | 7.0   | 3080  | 1.1664          | 0.8537   |
| 0.0732        | 8.0   | 3520  | 1.1017          | 0.7805   |
| 0.008         | 9.0   | 3960  | 1.1398          | 0.8049   |
| 0.0271        | 10.0  | 4400  | 1.5569          | 0.7805   |
| 0.0842        | 11.0  | 4840  | 1.2296          | 0.7561   |
| 0.118         | 12.0  | 5280  | 1.2857          | 0.7561   |
| 0.1189        | 13.0  | 5720  | 1.5541          | 0.7805   |
| 0.0212        | 14.0  | 6160  | 1.5600          | 0.7561   |
| 0.0002        | 15.0  | 6600  | 1.5864          | 0.7805   |
| 0.0255        | 16.0  | 7040  | 2.2625          | 0.8293   |
| 0.0909        | 17.0  | 7480  | 1.7777          | 0.7805   |
| 0.0006        | 18.0  | 7920  | 2.1059          | 0.7805   |
| 0.0539        | 19.0  | 8360  | 1.1345          | 0.8537   |
| 0.0127        | 20.0  | 8800  | 1.9942          | 0.8049   |
| 0.0316        | 21.0  | 9240  | 1.1699          | 0.7805   |
| 0.0099        | 22.0  | 9680  | 1.7444          | 0.7805   |
| 0.0006        | 23.0  | 10120 | 1.4208          | 0.7805   |
| 0.0023        | 24.0  | 10560 | 1.5828          | 0.8780   |
| 0.0338        | 25.0  | 11000 | 1.8683          | 0.8537   |
| 0.0001        | 26.0  | 11440 | 2.1797          | 0.7805   |
| 0.0456        | 27.0  | 11880 | 2.7058          | 0.7561   |
| 0.0372        | 28.0  | 12320 | 1.7549          | 0.8049   |
| 0.0503        | 29.0  | 12760 | 1.4924          | 0.8537   |
| 0.0422        | 30.0  | 13200 | 1.1164          | 0.8293   |
| 0.0           | 31.0  | 13640 | 2.3328          | 0.7317   |
| 0.0332        | 32.0  | 14080 | 1.6999          | 0.7805   |
| 0.0436        | 33.0  | 14520 | 1.4780          | 0.8293   |
| 0.0351        | 34.0  | 14960 | 2.6321          | 0.6829   |
| 0.0001        | 35.0  | 15400 | 1.8713          | 0.7805   |
| 0.0           | 36.0  | 15840 | 2.2223          | 0.7805   |
| 0.0147        | 37.0  | 16280 | 2.4217          | 0.7805   |
| 0.0           | 38.0  | 16720 | 2.3800          | 0.7561   |
| 0.0           | 39.0  | 17160 | 1.6116          | 0.7805   |
| 0.0385        | 40.0  | 17600 | 2.0402          | 0.8049   |
| 0.0           | 41.0  | 18040 | 2.1894          | 0.7561   |
| 0.0001        | 42.0  | 18480 | 2.1455          | 0.7805   |
| 0.0           | 43.0  | 18920 | 1.9871          | 0.7561   |
| 0.0           | 44.0  | 19360 | 2.0740          | 0.8049   |
| 0.0           | 45.0  | 19800 | 2.3467          | 0.7561   |
| 0.0           | 46.0  | 20240 | 2.5948          | 0.7805   |
| 0.0           | 47.0  | 20680 | 2.4493          | 0.8049   |
| 0.0           | 48.0  | 21120 | 2.5365          | 0.8049   |
| 0.0           | 49.0  | 21560 | 2.7623          | 0.7805   |
| 0.0           | 50.0  | 22000 | 2.7065          | 0.7805   |


### 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_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7804878048780488, "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