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# HUSHEM_10x_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: 0.4110
- Accuracy: 0.9024

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0778        | 1.0   | 110  | 0.4033          | 0.8537   |
| 0.0024        | 2.0   | 220  | 0.7189          | 0.8049   |
| 0.0001        | 3.0   | 330  | 0.6054          | 0.8293   |
| 0.0249        | 4.0   | 440  | 0.8501          | 0.8537   |
| 0.0001        | 5.0   | 550  | 0.3205          | 0.9024   |
| 0.0001        | 6.0   | 660  | 0.4612          | 0.8780   |
| 0.0017        | 7.0   | 770  | 1.0256          | 0.8049   |
| 0.0001        | 8.0   | 880  | 0.4001          | 0.9024   |
| 0.0           | 9.0   | 990  | 0.7009          | 0.8537   |
| 0.0001        | 10.0  | 1100 | 0.4361          | 0.8780   |
| 0.0           | 11.0  | 1210 | 0.5472          | 0.8780   |
| 0.0           | 12.0  | 1320 | 0.6296          | 0.8780   |
| 0.0           | 13.0  | 1430 | 1.0038          | 0.8293   |
| 0.0002        | 14.0  | 1540 | 0.4220          | 0.9268   |
| 0.0           | 15.0  | 1650 | 0.5056          | 0.9268   |
| 0.0           | 16.0  | 1760 | 1.1459          | 0.8293   |
| 0.0           | 17.0  | 1870 | 1.2065          | 0.8293   |
| 0.0076        | 18.0  | 1980 | 0.8258          | 0.8537   |
| 0.0           | 19.0  | 2090 | 0.7600          | 0.8537   |
| 0.0           | 20.0  | 2200 | 0.6026          | 0.8537   |
| 0.0           | 21.0  | 2310 | 0.6438          | 0.8537   |
| 0.0167        | 22.0  | 2420 | 0.3730          | 0.9024   |
| 0.0           | 23.0  | 2530 | 0.4689          | 0.8780   |
| 0.0           | 24.0  | 2640 | 0.7419          | 0.8293   |
| 0.0           | 25.0  | 2750 | 0.5106          | 0.9024   |
| 0.0           | 26.0  | 2860 | 0.5175          | 0.8780   |
| 0.0           | 27.0  | 2970 | 0.4947          | 0.8780   |
| 0.0           | 28.0  | 3080 | 0.8319          | 0.8537   |
| 0.0           | 29.0  | 3190 | 0.7281          | 0.8293   |
| 0.0           | 30.0  | 3300 | 0.4797          | 0.8537   |
| 0.0           | 31.0  | 3410 | 0.5058          | 0.8537   |
| 0.0           | 32.0  | 3520 | 0.5145          | 0.8537   |
| 0.0           | 33.0  | 3630 | 0.6408          | 0.8537   |
| 0.0           | 34.0  | 3740 | 0.4080          | 0.9024   |
| 0.0           | 35.0  | 3850 | 0.3923          | 0.9024   |
| 0.0           | 36.0  | 3960 | 0.3931          | 0.9024   |
| 0.0           | 37.0  | 4070 | 0.3957          | 0.9024   |
| 0.0           | 38.0  | 4180 | 0.4060          | 0.9024   |
| 0.0003        | 39.0  | 4290 | 1.1413          | 0.8293   |
| 0.0           | 40.0  | 4400 | 0.3903          | 0.9268   |
| 0.0           | 41.0  | 4510 | 0.3781          | 0.9268   |
| 0.0           | 42.0  | 4620 | 0.3785          | 0.9268   |
| 0.0           | 43.0  | 4730 | 0.3775          | 0.9268   |
| 0.0           | 44.0  | 4840 | 0.4411          | 0.9024   |
| 0.0           | 45.0  | 4950 | 0.4396          | 0.9024   |
| 0.0           | 46.0  | 5060 | 0.4297          | 0.9024   |
| 0.0           | 47.0  | 5170 | 0.4287          | 0.9024   |
| 0.0           | 48.0  | 5280 | 0.4072          | 0.9024   |
| 0.0           | 49.0  | 5390 | 0.4099          | 0.9024   |
| 0.0           | 50.0  | 5500 | 0.4110          | 0.9024   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "HUSHEM_10x_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": 0.9024390243902439, "name": "Accuracy"}]}]}]}
transformers pytorch 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