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# hushem_5x_beit_base_rms_001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7933
- Accuracy: 0.4444

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4827        | 1.0   | 27   | 1.4775          | 0.2444   |
| 1.4158        | 2.0   | 54   | 1.4002          | 0.2667   |
| 1.3654        | 3.0   | 81   | 1.4674          | 0.2444   |
| 1.4175        | 4.0   | 108  | 1.4412          | 0.2444   |
| 1.394         | 5.0   | 135  | 1.3951          | 0.2667   |
| 1.2686        | 6.0   | 162  | 1.3983          | 0.2444   |
| 1.2556        | 7.0   | 189  | 1.4175          | 0.2889   |
| 1.2245        | 8.0   | 216  | 1.4754          | 0.2222   |
| 1.1427        | 9.0   | 243  | 1.5387          | 0.2      |
| 1.1659        | 10.0  | 270  | 1.3896          | 0.3333   |
| 1.2047        | 11.0  | 297  | 1.6922          | 0.2444   |
| 1.1384        | 12.0  | 324  | 1.4940          | 0.2667   |
| 1.1563        | 13.0  | 351  | 1.3730          | 0.2889   |
| 1.1141        | 14.0  | 378  | 1.4944          | 0.2222   |
| 1.0922        | 15.0  | 405  | 1.4049          | 0.2222   |
| 1.0475        | 16.0  | 432  | 1.2541          | 0.4      |
| 0.9208        | 17.0  | 459  | 1.2993          | 0.4222   |
| 0.9847        | 18.0  | 486  | 1.4111          | 0.4889   |
| 0.9327        | 19.0  | 513  | 1.3175          | 0.2889   |
| 0.8591        | 20.0  | 540  | 1.2892          | 0.3111   |
| 0.7605        | 21.0  | 567  | 1.6440          | 0.2667   |
| 0.7953        | 22.0  | 594  | 1.6915          | 0.3778   |
| 0.7644        | 23.0  | 621  | 1.6017          | 0.4667   |
| 0.7884        | 24.0  | 648  | 1.4064          | 0.2444   |
| 0.6883        | 25.0  | 675  | 1.9722          | 0.3111   |
| 0.7747        | 26.0  | 702  | 1.9209          | 0.4889   |
| 0.7012        | 27.0  | 729  | 2.2074          | 0.5333   |
| 0.6951        | 28.0  | 756  | 2.4602          | 0.3556   |
| 0.6581        | 29.0  | 783  | 2.1544          | 0.4222   |
| 0.6529        | 30.0  | 810  | 2.0677          | 0.3556   |
| 0.533         | 31.0  | 837  | 2.1507          | 0.3778   |
| 0.6648        | 32.0  | 864  | 2.1628          | 0.4222   |
| 0.6094        | 33.0  | 891  | 2.5365          | 0.3778   |
| 0.5601        | 34.0  | 918  | 2.8323          | 0.4222   |
| 0.519         | 35.0  | 945  | 2.4166          | 0.4      |
| 0.5988        | 36.0  | 972  | 2.6302          | 0.4444   |
| 0.5359        | 37.0  | 999  | 2.9183          | 0.3778   |
| 0.5451        | 38.0  | 1026 | 2.8746          | 0.5111   |
| 0.5087        | 39.0  | 1053 | 2.7419          | 0.4667   |
| 0.4563        | 40.0  | 1080 | 3.1565          | 0.4222   |
| 0.5182        | 41.0  | 1107 | 3.1768          | 0.4444   |
| 0.4348        | 42.0  | 1134 | 3.2761          | 0.4222   |
| 0.4504        | 43.0  | 1161 | 3.4108          | 0.4667   |
| 0.417         | 44.0  | 1188 | 3.5781          | 0.4444   |
| 0.4297        | 45.0  | 1215 | 3.6284          | 0.4444   |
| 0.3399        | 46.0  | 1242 | 3.7187          | 0.4444   |
| 0.3846        | 47.0  | 1269 | 3.7298          | 0.4667   |
| 0.3494        | 48.0  | 1296 | 3.7854          | 0.4444   |
| 0.3468        | 49.0  | 1323 | 3.7933          | 0.4444   |
| 0.3313        | 50.0  | 1350 | 3.7933          | 0.4444   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_rms_001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.4444444444444444, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us