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# HUSHEM_10x_beit_large_RMSProp_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: 2.4259
- Accuracy: 0.7317

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.388         | 1.0   | 110  | 1.4171          | 0.2683   |
| 1.3821        | 2.0   | 220  | 1.4561          | 0.2439   |
| 1.3717        | 3.0   | 330  | 1.3780          | 0.4878   |
| 1.3735        | 4.0   | 440  | 1.3217          | 0.3659   |
| 1.2786        | 5.0   | 550  | 1.2694          | 0.4878   |
| 1.2335        | 6.0   | 660  | 1.2677          | 0.4878   |
| 1.2681        | 7.0   | 770  | 1.4575          | 0.5122   |
| 1.4406        | 8.0   | 880  | 1.3574          | 0.3659   |
| 1.3027        | 9.0   | 990  | 1.2429          | 0.5122   |
| 1.1876        | 10.0  | 1100 | 1.2268          | 0.4878   |
| 1.2346        | 11.0  | 1210 | 1.2311          | 0.4634   |
| 1.239         | 12.0  | 1320 | 1.0478          | 0.4390   |
| 1.1865        | 13.0  | 1430 | 1.1016          | 0.4878   |
| 1.0542        | 14.0  | 1540 | 0.9191          | 0.6341   |
| 0.9639        | 15.0  | 1650 | 1.0119          | 0.5854   |
| 1.1739        | 16.0  | 1760 | 0.8146          | 0.6341   |
| 0.9451        | 17.0  | 1870 | 1.0025          | 0.6341   |
| 0.8678        | 18.0  | 1980 | 1.0008          | 0.6585   |
| 0.7926        | 19.0  | 2090 | 0.9860          | 0.6585   |
| 0.7577        | 20.0  | 2200 | 0.9502          | 0.5366   |
| 0.6012        | 21.0  | 2310 | 0.9917          | 0.6829   |
| 0.6445        | 22.0  | 2420 | 1.2231          | 0.5122   |
| 0.7461        | 23.0  | 2530 | 1.0053          | 0.7073   |
| 0.6249        | 24.0  | 2640 | 1.4753          | 0.5366   |
| 0.6758        | 25.0  | 2750 | 1.0938          | 0.5854   |
| 0.6191        | 26.0  | 2860 | 0.8225          | 0.6341   |
| 0.5668        | 27.0  | 2970 | 0.9099          | 0.6585   |
| 0.5524        | 28.0  | 3080 | 0.9137          | 0.6829   |
| 0.5282        | 29.0  | 3190 | 1.1310          | 0.6098   |
| 0.459         | 30.0  | 3300 | 1.0865          | 0.6341   |
| 0.4277        | 31.0  | 3410 | 0.9904          | 0.6585   |
| 0.3997        | 32.0  | 3520 | 0.9150          | 0.6829   |
| 0.3131        | 33.0  | 3630 | 1.0186          | 0.6829   |
| 0.4497        | 34.0  | 3740 | 1.2371          | 0.6098   |
| 0.2816        | 35.0  | 3850 | 0.8543          | 0.7317   |
| 0.2206        | 36.0  | 3960 | 1.1120          | 0.7073   |
| 0.1944        | 37.0  | 4070 | 1.3150          | 0.7073   |
| 0.1457        | 38.0  | 4180 | 1.8032          | 0.5854   |
| 0.1947        | 39.0  | 4290 | 1.3111          | 0.6585   |
| 0.2775        | 40.0  | 4400 | 1.6032          | 0.7073   |
| 0.225         | 41.0  | 4510 | 1.6995          | 0.6829   |
| 0.1           | 42.0  | 4620 | 1.5794          | 0.6585   |
| 0.241         | 43.0  | 4730 | 1.6058          | 0.6585   |
| 0.054         | 44.0  | 4840 | 1.8383          | 0.7317   |
| 0.1427        | 45.0  | 4950 | 2.2715          | 0.7317   |
| 0.0802        | 46.0  | 5060 | 2.5099          | 0.6829   |
| 0.07          | 47.0  | 5170 | 2.2911          | 0.7317   |
| 0.2006        | 48.0  | 5280 | 2.1692          | 0.7317   |
| 0.0356        | 49.0  | 5390 | 2.3696          | 0.7317   |
| 0.0415        | 50.0  | 5500 | 2.4259          | 0.7317   |


### 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_10x_beit_large_RMSProp_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": 0.7317073170731707, "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