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# HUSHEM_5x_beit_large_Adamax_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: 4.4292
- Accuracy: 0.6341

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4434        | 1.0   | 55   | 1.4192          | 0.2439   |
| 1.1512        | 2.0   | 110  | 1.0520          | 0.6098   |
| 1.1055        | 3.0   | 165  | 0.8247          | 0.6098   |
| 1.0001        | 4.0   | 220  | 1.0953          | 0.6585   |
| 1.0393        | 5.0   | 275  | 0.9491          | 0.6341   |
| 0.9331        | 6.0   | 330  | 1.4336          | 0.6341   |
| 1.0071        | 7.0   | 385  | 0.6915          | 0.7805   |
| 0.8126        | 8.0   | 440  | 0.8558          | 0.7073   |
| 0.8987        | 9.0   | 495  | 0.9067          | 0.6585   |
| 0.7918        | 10.0  | 550  | 0.9970          | 0.7317   |
| 0.7255        | 11.0  | 605  | 0.7997          | 0.7317   |
| 0.8439        | 12.0  | 660  | 0.7828          | 0.7073   |
| 0.739         | 13.0  | 715  | 0.9609          | 0.6341   |
| 0.6585        | 14.0  | 770  | 1.0059          | 0.6829   |
| 0.7265        | 15.0  | 825  | 1.1440          | 0.5854   |
| 0.6206        | 16.0  | 880  | 1.0972          | 0.6829   |
| 0.6275        | 17.0  | 935  | 1.4890          | 0.6829   |
| 0.6096        | 18.0  | 990  | 0.9349          | 0.7073   |
| 0.5917        | 19.0  | 1045 | 1.1786          | 0.6341   |
| 0.5347        | 20.0  | 1100 | 0.9257          | 0.7073   |
| 0.4572        | 21.0  | 1155 | 1.1154          | 0.7073   |
| 0.4081        | 22.0  | 1210 | 1.4984          | 0.6585   |
| 0.3798        | 23.0  | 1265 | 1.6072          | 0.7317   |
| 0.2822        | 24.0  | 1320 | 1.4180          | 0.6829   |
| 0.2546        | 25.0  | 1375 | 1.7684          | 0.6585   |
| 0.4326        | 26.0  | 1430 | 1.9163          | 0.5854   |
| 0.2066        | 27.0  | 1485 | 2.5230          | 0.6098   |
| 0.1854        | 28.0  | 1540 | 2.4137          | 0.6341   |
| 0.2496        | 29.0  | 1595 | 1.6709          | 0.6585   |
| 0.2783        | 30.0  | 1650 | 1.7229          | 0.7073   |
| 0.4096        | 31.0  | 1705 | 1.7701          | 0.7561   |
| 0.1093        | 32.0  | 1760 | 3.0338          | 0.6585   |
| 0.1804        | 33.0  | 1815 | 2.2574          | 0.6585   |
| 0.0709        | 34.0  | 1870 | 3.3220          | 0.6585   |
| 0.1391        | 35.0  | 1925 | 3.7920          | 0.6098   |
| 0.0511        | 36.0  | 1980 | 4.0606          | 0.6341   |
| 0.1621        | 37.0  | 2035 | 3.7421          | 0.6829   |
| 0.0276        | 38.0  | 2090 | 3.8459          | 0.6098   |
| 0.0528        | 39.0  | 2145 | 3.3461          | 0.6585   |
| 0.0031        | 40.0  | 2200 | 3.4932          | 0.6585   |
| 0.0276        | 41.0  | 2255 | 3.8803          | 0.5610   |
| 0.0025        | 42.0  | 2310 | 3.6038          | 0.6829   |
| 0.0771        | 43.0  | 2365 | 4.0608          | 0.6098   |
| 0.0091        | 44.0  | 2420 | 4.1920          | 0.5854   |
| 0.0512        | 45.0  | 2475 | 3.9272          | 0.6098   |
| 0.0136        | 46.0  | 2530 | 4.2749          | 0.6098   |
| 0.0003        | 47.0  | 2585 | 4.3035          | 0.6341   |
| 0.0081        | 48.0  | 2640 | 4.4142          | 0.6341   |
| 0.0033        | 49.0  | 2695 | 4.4306          | 0.6341   |
| 0.0069        | 50.0  | 2750 | 4.4292          | 0.6341   |


### 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_Adamax_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": 0.6341463414634146, "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