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# HUSHEM_10x_beit_large_Adamax_lr0001_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: 0.5351
- Accuracy: 0.8780

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0933        | 1.0   | 110  | 0.8433          | 0.8293   |
| 0.0122        | 2.0   | 220  | 0.2069          | 0.9024   |
| 0.0004        | 3.0   | 330  | 0.6970          | 0.9024   |
| 0.0041        | 4.0   | 440  | 1.2514          | 0.8293   |
| 0.0009        | 5.0   | 550  | 1.1106          | 0.8537   |
| 0.0287        | 6.0   | 660  | 1.5018          | 0.7561   |
| 0.0002        | 7.0   | 770  | 1.3912          | 0.7561   |
| 0.0           | 8.0   | 880  | 1.1803          | 0.8293   |
| 0.0           | 9.0   | 990  | 1.3345          | 0.8537   |
| 0.0           | 10.0  | 1100 | 0.8867          | 0.8537   |
| 0.0002        | 11.0  | 1210 | 0.6185          | 0.9024   |
| 0.0125        | 12.0  | 1320 | 1.2476          | 0.7805   |
| 0.0           | 13.0  | 1430 | 0.9339          | 0.8293   |
| 0.0           | 14.0  | 1540 | 0.7033          | 0.8537   |
| 0.0           | 15.0  | 1650 | 0.6530          | 0.8537   |
| 0.0           | 16.0  | 1760 | 0.6316          | 0.8537   |
| 0.0           | 17.0  | 1870 | 0.6034          | 0.8537   |
| 0.0           | 18.0  | 1980 | 0.5904          | 0.8537   |
| 0.0           | 19.0  | 2090 | 0.5957          | 0.8537   |
| 0.0           | 20.0  | 2200 | 0.5890          | 0.8537   |
| 0.0           | 21.0  | 2310 | 0.5782          | 0.8537   |
| 0.0           | 22.0  | 2420 | 0.5754          | 0.8537   |
| 0.0           | 23.0  | 2530 | 0.5686          | 0.8537   |
| 0.0           | 24.0  | 2640 | 0.5749          | 0.8537   |
| 0.0           | 25.0  | 2750 | 0.5860          | 0.8537   |
| 0.0           | 26.0  | 2860 | 0.5781          | 0.8537   |
| 0.0           | 27.0  | 2970 | 0.5772          | 0.8537   |
| 0.0           | 28.0  | 3080 | 0.5843          | 0.8537   |
| 0.0           | 29.0  | 3190 | 0.5813          | 0.8537   |
| 0.0           | 30.0  | 3300 | 0.8887          | 0.8293   |
| 0.0           | 31.0  | 3410 | 0.7726          | 0.8537   |
| 0.0           | 32.0  | 3520 | 0.7971          | 0.8293   |
| 0.0           | 33.0  | 3630 | 0.6464          | 0.8537   |
| 0.0           | 34.0  | 3740 | 0.6314          | 0.8537   |
| 0.0           | 35.0  | 3850 | 0.6241          | 0.8537   |
| 0.0           | 36.0  | 3960 | 0.6319          | 0.8537   |
| 0.0           | 37.0  | 4070 | 0.6273          | 0.8537   |
| 0.0           | 38.0  | 4180 | 0.6220          | 0.8537   |
| 0.0           | 39.0  | 4290 | 0.6192          | 0.8537   |
| 0.0           | 40.0  | 4400 | 0.6187          | 0.8537   |
| 0.0           | 41.0  | 4510 | 0.5213          | 0.8780   |
| 0.0           | 42.0  | 4620 | 0.5139          | 0.8780   |
| 0.0           | 43.0  | 4730 | 0.5185          | 0.8780   |
| 0.0           | 44.0  | 4840 | 0.5224          | 0.8780   |
| 0.0           | 45.0  | 4950 | 0.5274          | 0.8780   |
| 0.0           | 46.0  | 5060 | 0.5332          | 0.8780   |
| 0.0           | 47.0  | 5170 | 0.5335          | 0.8780   |
| 0.0           | 48.0  | 5280 | 0.5351          | 0.8780   |
| 0.0           | 49.0  | 5390 | 0.5351          | 0.8780   |
| 0.0           | 50.0  | 5500 | 0.5351          | 0.8780   |


### 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_10x_beit_large_Adamax_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8780487804878049, "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