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# HUSHEM_5x_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: 1.6285
- Accuracy: 0.6905

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4104        | 1.0   | 55   | 1.3898          | 0.2381   |
| 1.3906        | 2.0   | 110  | 1.3834          | 0.2619   |
| 1.3882        | 3.0   | 165  | 1.4129          | 0.2381   |
| 1.376         | 4.0   | 220  | 1.3377          | 0.2381   |
| 1.3782        | 5.0   | 275  | 1.3818          | 0.2619   |
| 1.5568        | 6.0   | 330  | 1.3579          | 0.2619   |
| 1.3948        | 7.0   | 385  | 1.3471          | 0.2619   |
| 1.3395        | 8.0   | 440  | 0.9877          | 0.6429   |
| 1.2071        | 9.0   | 495  | 1.1028          | 0.4048   |
| 1.1735        | 10.0  | 550  | 1.0171          | 0.5238   |
| 1.0588        | 11.0  | 605  | 0.8007          | 0.7143   |
| 1.1049        | 12.0  | 660  | 0.7601          | 0.7143   |
| 1.0816        | 13.0  | 715  | 0.9175          | 0.6190   |
| 1.0945        | 14.0  | 770  | 0.9530          | 0.7143   |
| 1.0943        | 15.0  | 825  | 0.8020          | 0.7143   |
| 0.8623        | 16.0  | 880  | 0.9797          | 0.6190   |
| 0.9432        | 17.0  | 935  | 0.7487          | 0.7381   |
| 0.7801        | 18.0  | 990  | 0.7999          | 0.7143   |
| 0.9711        | 19.0  | 1045 | 0.7903          | 0.7143   |
| 0.946         | 20.0  | 1100 | 0.7494          | 0.6905   |
| 0.9325        | 21.0  | 1155 | 0.7495          | 0.7619   |
| 0.8398        | 22.0  | 1210 | 0.8115          | 0.8095   |
| 0.8707        | 23.0  | 1265 | 0.8391          | 0.7381   |
| 0.8531        | 24.0  | 1320 | 0.8129          | 0.7381   |
| 0.7878        | 25.0  | 1375 | 0.7796          | 0.6905   |
| 0.9239        | 26.0  | 1430 | 0.8091          | 0.7143   |
| 0.775         | 27.0  | 1485 | 0.8655          | 0.5952   |
| 0.8082        | 28.0  | 1540 | 0.7866          | 0.6667   |
| 0.8856        | 29.0  | 1595 | 1.0078          | 0.6905   |
| 0.7987        | 30.0  | 1650 | 0.9091          | 0.7381   |
| 0.8648        | 31.0  | 1705 | 0.7940          | 0.7619   |
| 0.9571        | 32.0  | 1760 | 0.7467          | 0.6905   |
| 0.7849        | 33.0  | 1815 | 0.9430          | 0.6667   |
| 0.9049        | 34.0  | 1870 | 0.8616          | 0.7143   |
| 0.7838        | 35.0  | 1925 | 0.8524          | 0.7143   |
| 0.6536        | 36.0  | 1980 | 1.1943          | 0.6667   |
| 0.7657        | 37.0  | 2035 | 1.0510          | 0.7143   |
| 0.666         | 38.0  | 2090 | 0.9268          | 0.7619   |
| 0.6934        | 39.0  | 2145 | 0.9907          | 0.7381   |
| 0.6093        | 40.0  | 2200 | 0.9615          | 0.7143   |
| 0.6316        | 41.0  | 2255 | 1.1143          | 0.7143   |
| 0.6475        | 42.0  | 2310 | 1.1557          | 0.6905   |
| 0.6351        | 43.0  | 2365 | 1.3359          | 0.7143   |
| 0.5829        | 44.0  | 2420 | 1.4745          | 0.7381   |
| 0.4078        | 45.0  | 2475 | 1.4548          | 0.6667   |
| 0.6048        | 46.0  | 2530 | 1.7216          | 0.7143   |
| 0.512         | 47.0  | 2585 | 1.6270          | 0.6905   |
| 0.3864        | 48.0  | 2640 | 1.5658          | 0.6905   |
| 0.3247        | 49.0  | 2695 | 1.6276          | 0.6905   |
| 0.3115        | 50.0  | 2750 | 1.6285          | 0.6905   |


### 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_5x_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": 0.6904761904761905, "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