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# HUSHEM_5x_beit_large_Adamax_lr001_fold3

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: 3.1097
- Accuracy: 0.7442

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3998        | 1.0   | 55   | 1.2515          | 0.4884   |
| 1.3257        | 2.0   | 110  | 1.2450          | 0.5814   |
| 0.8915        | 3.0   | 165  | 1.3022          | 0.3023   |
| 0.9028        | 4.0   | 220  | 1.3282          | 0.5116   |
| 0.8295        | 5.0   | 275  | 1.2421          | 0.4419   |
| 1.0552        | 6.0   | 330  | 0.8658          | 0.6977   |
| 0.9263        | 7.0   | 385  | 0.7528          | 0.6279   |
| 0.8658        | 8.0   | 440  | 0.6988          | 0.7442   |
| 0.7961        | 9.0   | 495  | 0.7690          | 0.6977   |
| 0.7919        | 10.0  | 550  | 0.7036          | 0.8372   |
| 0.7364        | 11.0  | 605  | 1.3367          | 0.5116   |
| 0.724         | 12.0  | 660  | 0.6808          | 0.6047   |
| 0.6814        | 13.0  | 715  | 0.7730          | 0.6977   |
| 0.6247        | 14.0  | 770  | 0.8897          | 0.7209   |
| 0.6948        | 15.0  | 825  | 0.9793          | 0.5581   |
| 0.4669        | 16.0  | 880  | 1.0567          | 0.6047   |
| 0.5713        | 17.0  | 935  | 1.3460          | 0.5581   |
| 0.3654        | 18.0  | 990  | 1.6314          | 0.4884   |
| 0.4398        | 19.0  | 1045 | 1.1734          | 0.6047   |
| 0.469         | 20.0  | 1100 | 0.9193          | 0.6977   |
| 0.4317        | 21.0  | 1155 | 1.2389          | 0.6744   |
| 0.4363        | 22.0  | 1210 | 1.4680          | 0.6047   |
| 0.3069        | 23.0  | 1265 | 1.3032          | 0.6279   |
| 0.2727        | 24.0  | 1320 | 1.5400          | 0.5814   |
| 0.4601        | 25.0  | 1375 | 1.6924          | 0.6047   |
| 0.3694        | 26.0  | 1430 | 1.6714          | 0.6047   |
| 0.2782        | 27.0  | 1485 | 1.6149          | 0.6512   |
| 0.2567        | 28.0  | 1540 | 2.3240          | 0.6047   |
| 0.6074        | 29.0  | 1595 | 2.1192          | 0.6279   |
| 0.2281        | 30.0  | 1650 | 1.8471          | 0.6744   |
| 0.1915        | 31.0  | 1705 | 1.9120          | 0.6512   |
| 0.2371        | 32.0  | 1760 | 2.8160          | 0.6047   |
| 0.1354        | 33.0  | 1815 | 3.0628          | 0.6279   |
| 0.1908        | 34.0  | 1870 | 3.8978          | 0.6744   |
| 0.2414        | 35.0  | 1925 | 3.4798          | 0.6977   |
| 0.1558        | 36.0  | 1980 | 3.8206          | 0.6977   |
| 0.0899        | 37.0  | 2035 | 3.2284          | 0.6744   |
| 0.0422        | 38.0  | 2090 | 4.1352          | 0.6512   |
| 0.0257        | 39.0  | 2145 | 3.8848          | 0.6977   |
| 0.0131        | 40.0  | 2200 | 3.4923          | 0.6977   |
| 0.0615        | 41.0  | 2255 | 3.3086          | 0.6977   |
| 0.0527        | 42.0  | 2310 | 3.5180          | 0.6977   |
| 0.0483        | 43.0  | 2365 | 3.2072          | 0.6977   |
| 0.0005        | 44.0  | 2420 | 3.2087          | 0.7209   |
| 0.0084        | 45.0  | 2475 | 3.2656          | 0.6744   |
| 0.0015        | 46.0  | 2530 | 3.0759          | 0.7442   |
| 0.0356        | 47.0  | 2585 | 3.1244          | 0.7209   |
| 0.0106        | 48.0  | 2640 | 3.0763          | 0.7442   |
| 0.1019        | 49.0  | 2695 | 3.1098          | 0.7442   |
| 0.0104        | 50.0  | 2750 | 3.1097          | 0.7442   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7441860465116279, "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