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# HUSHEM_5x_beit_large_SGD_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: 0.5851
- Accuracy: 0.7857

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5894        | 1.0   | 55   | 1.4195          | 0.3095   |
| 1.4438        | 2.0   | 110  | 1.3343          | 0.3095   |
| 1.3609        | 3.0   | 165  | 1.2751          | 0.3810   |
| 1.2359        | 4.0   | 220  | 1.2208          | 0.4762   |
| 1.1842        | 5.0   | 275  | 1.1696          | 0.5238   |
| 1.0119        | 6.0   | 330  | 1.1259          | 0.5476   |
| 1.0933        | 7.0   | 385  | 1.0882          | 0.5952   |
| 1.0806        | 8.0   | 440  | 1.0496          | 0.5952   |
| 0.9825        | 9.0   | 495  | 1.0151          | 0.5952   |
| 0.8992        | 10.0  | 550  | 0.9791          | 0.6190   |
| 0.8237        | 11.0  | 605  | 0.9484          | 0.6190   |
| 0.8166        | 12.0  | 660  | 0.9199          | 0.6429   |
| 0.7925        | 13.0  | 715  | 0.8914          | 0.6429   |
| 0.712         | 14.0  | 770  | 0.8661          | 0.6429   |
| 0.7093        | 15.0  | 825  | 0.8402          | 0.6667   |
| 0.717         | 16.0  | 880  | 0.8113          | 0.6905   |
| 0.7325        | 17.0  | 935  | 0.7905          | 0.7143   |
| 0.6254        | 18.0  | 990  | 0.7745          | 0.7381   |
| 0.6644        | 19.0  | 1045 | 0.7598          | 0.7381   |
| 0.6482        | 20.0  | 1100 | 0.7442          | 0.7381   |
| 0.641         | 21.0  | 1155 | 0.7338          | 0.7143   |
| 0.6048        | 22.0  | 1210 | 0.7157          | 0.7381   |
| 0.5575        | 23.0  | 1265 | 0.7088          | 0.7381   |
| 0.6059        | 24.0  | 1320 | 0.6966          | 0.7381   |
| 0.5076        | 25.0  | 1375 | 0.6837          | 0.7381   |
| 0.5744        | 26.0  | 1430 | 0.6745          | 0.7381   |
| 0.4899        | 27.0  | 1485 | 0.6670          | 0.7381   |
| 0.4974        | 28.0  | 1540 | 0.6604          | 0.7619   |
| 0.5028        | 29.0  | 1595 | 0.6570          | 0.7619   |
| 0.4845        | 30.0  | 1650 | 0.6481          | 0.7619   |
| 0.4758        | 31.0  | 1705 | 0.6380          | 0.7619   |
| 0.5081        | 32.0  | 1760 | 0.6287          | 0.7857   |
| 0.4685        | 33.0  | 1815 | 0.6241          | 0.7857   |
| 0.5278        | 34.0  | 1870 | 0.6227          | 0.7857   |
| 0.4415        | 35.0  | 1925 | 0.6181          | 0.7857   |
| 0.4982        | 36.0  | 1980 | 0.6091          | 0.7857   |
| 0.4481        | 37.0  | 2035 | 0.6094          | 0.7857   |
| 0.4246        | 38.0  | 2090 | 0.6041          | 0.7857   |
| 0.4558        | 39.0  | 2145 | 0.5966          | 0.7857   |
| 0.4431        | 40.0  | 2200 | 0.5949          | 0.7857   |
| 0.3714        | 41.0  | 2255 | 0.5912          | 0.7857   |
| 0.3939        | 42.0  | 2310 | 0.5880          | 0.7857   |
| 0.4033        | 43.0  | 2365 | 0.5884          | 0.7857   |
| 0.4483        | 44.0  | 2420 | 0.5879          | 0.7857   |
| 0.3866        | 45.0  | 2475 | 0.5868          | 0.7857   |
| 0.4075        | 46.0  | 2530 | 0.5862          | 0.7857   |
| 0.4122        | 47.0  | 2585 | 0.5860          | 0.7857   |
| 0.3812        | 48.0  | 2640 | 0.5853          | 0.7857   |
| 0.4465        | 49.0  | 2695 | 0.5851          | 0.7857   |
| 0.3791        | 50.0  | 2750 | 0.5851          | 0.7857   |


### 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_5x_beit_large_SGD_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": 0.7857142857142857, "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