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# hushem_40x_beit_large_rmsprop_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: 1.7160
- Accuracy: 0.8293

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8356        | 1.0   | 440   | 0.9226          | 0.5610   |
| 0.6556        | 2.0   | 880   | 0.9637          | 0.6098   |
| 0.6643        | 3.0   | 1320  | 1.3666          | 0.5610   |
| 0.5961        | 4.0   | 1760  | 0.3460          | 0.8780   |
| 0.3997        | 5.0   | 2200  | 0.7718          | 0.8049   |
| 0.2263        | 6.0   | 2640  | 0.2625          | 0.8780   |
| 0.162         | 7.0   | 3080  | 0.6107          | 0.8537   |
| 0.1685        | 8.0   | 3520  | 0.4891          | 0.8537   |
| 0.3326        | 9.0   | 3960  | 0.7202          | 0.7317   |
| 0.0551        | 10.0  | 4400  | 0.6191          | 0.8537   |
| 0.1383        | 11.0  | 4840  | 0.4852          | 0.8293   |
| 0.0455        | 12.0  | 5280  | 0.6118          | 0.8293   |
| 0.0122        | 13.0  | 5720  | 0.7489          | 0.8293   |
| 0.0161        | 14.0  | 6160  | 1.3931          | 0.8293   |
| 0.06          | 15.0  | 6600  | 0.9143          | 0.8293   |
| 0.007         | 16.0  | 7040  | 0.4026          | 0.8780   |
| 0.0449        | 17.0  | 7480  | 0.4407          | 0.9024   |
| 0.0025        | 18.0  | 7920  | 0.5968          | 0.9024   |
| 0.011         | 19.0  | 8360  | 0.7299          | 0.9024   |
| 0.0132        | 20.0  | 8800  | 0.8208          | 0.8780   |
| 0.0006        | 21.0  | 9240  | 0.9658          | 0.8537   |
| 0.0214        | 22.0  | 9680  | 0.7415          | 0.9024   |
| 0.001         | 23.0  | 10120 | 0.6217          | 0.8537   |
| 0.0004        | 24.0  | 10560 | 0.8488          | 0.8537   |
| 0.0002        | 25.0  | 11000 | 0.4806          | 0.9268   |
| 0.001         | 26.0  | 11440 | 0.6403          | 0.9024   |
| 0.0002        | 27.0  | 11880 | 0.9631          | 0.8537   |
| 0.0004        | 28.0  | 12320 | 0.9622          | 0.8780   |
| 0.0002        | 29.0  | 12760 | 0.8177          | 0.9024   |
| 0.001         | 30.0  | 13200 | 1.4185          | 0.7805   |
| 0.0001        | 31.0  | 13640 | 1.8113          | 0.8049   |
| 0.0078        | 32.0  | 14080 | 1.1339          | 0.8537   |
| 0.0022        | 33.0  | 14520 | 1.0634          | 0.8537   |
| 0.0015        | 34.0  | 14960 | 0.8414          | 0.8780   |
| 0.0001        | 35.0  | 15400 | 1.3464          | 0.8293   |
| 0.0017        | 36.0  | 15840 | 1.3216          | 0.8293   |
| 0.0002        | 37.0  | 16280 | 1.2986          | 0.8537   |
| 0.0           | 38.0  | 16720 | 1.5827          | 0.8049   |
| 0.0           | 39.0  | 17160 | 3.1309          | 0.7561   |
| 0.0           | 40.0  | 17600 | 1.2254          | 0.8537   |
| 0.0           | 41.0  | 18040 | 1.7105          | 0.8293   |
| 0.0           | 42.0  | 18480 | 1.2777          | 0.8537   |
| 0.0           | 43.0  | 18920 | 1.1163          | 0.8780   |
| 0.0           | 44.0  | 19360 | 1.3635          | 0.8293   |
| 0.0           | 45.0  | 19800 | 1.5911          | 0.8537   |
| 0.0002        | 46.0  | 20240 | 1.9159          | 0.8049   |
| 0.0           | 47.0  | 20680 | 1.2846          | 0.8780   |
| 0.0           | 48.0  | 21120 | 1.6036          | 0.8537   |
| 0.0           | 49.0  | 21560 | 1.7659          | 0.8049   |
| 0.0           | 50.0  | 22000 | 1.7160          | 0.8293   |


### 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_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8292682926829268, "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