
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# HUSHEM_5x_beit_large_Adamax_lr001_fold2

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: 7.2304
- Accuracy: 0.5111

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1857        | 1.0   | 54   | 1.5048          | 0.2889   |
| 1.1633        | 2.0   | 108  | 1.7462          | 0.2889   |
| 1.0677        | 3.0   | 162  | 1.3888          | 0.4667   |
| 0.9848        | 4.0   | 216  | 1.4956          | 0.3111   |
| 0.7714        | 5.0   | 270  | 1.8311          | 0.4889   |
| 0.7534        | 6.0   | 324  | 1.3714          | 0.4667   |
| 0.8436        | 7.0   | 378  | 1.6525          | 0.4889   |
| 0.7692        | 8.0   | 432  | 1.7698          | 0.4      |
| 0.5991        | 9.0   | 486  | 2.3426          | 0.5111   |
| 0.5887        | 10.0  | 540  | 2.3638          | 0.3778   |
| 0.8105        | 11.0  | 594  | 2.4960          | 0.5111   |
| 0.6053        | 12.0  | 648  | 2.2404          | 0.4667   |
| 0.5813        | 13.0  | 702  | 2.0257          | 0.4      |
| 0.6162        | 14.0  | 756  | 2.5823          | 0.4222   |
| 0.6489        | 15.0  | 810  | 2.7871          | 0.4444   |
| 0.3283        | 16.0  | 864  | 3.2811          | 0.4222   |
| 0.6566        | 17.0  | 918  | 2.4671          | 0.4      |
| 0.3904        | 18.0  | 972  | 3.1508          | 0.4667   |
| 0.3176        | 19.0  | 1026 | 3.4113          | 0.4222   |
| 0.361         | 20.0  | 1080 | 3.2955          | 0.4222   |
| 0.3132        | 21.0  | 1134 | 3.6032          | 0.5556   |
| 0.206         | 22.0  | 1188 | 3.4985          | 0.4889   |
| 0.2405        | 23.0  | 1242 | 3.3243          | 0.4444   |
| 0.1879        | 24.0  | 1296 | 4.0271          | 0.4889   |
| 0.1919        | 25.0  | 1350 | 4.9923          | 0.4444   |
| 0.1462        | 26.0  | 1404 | 4.6001          | 0.4667   |
| 0.1771        | 27.0  | 1458 | 5.3219          | 0.4444   |
| 0.1471        | 28.0  | 1512 | 4.8031          | 0.5333   |
| 0.2332        | 29.0  | 1566 | 4.8676          | 0.5556   |
| 0.1216        | 30.0  | 1620 | 5.2594          | 0.5333   |
| 0.2347        | 31.0  | 1674 | 5.9420          | 0.4667   |
| 0.1753        | 32.0  | 1728 | 5.3525          | 0.5111   |
| 0.0959        | 33.0  | 1782 | 6.6969          | 0.4889   |
| 0.0151        | 34.0  | 1836 | 7.2043          | 0.4889   |
| 0.0444        | 35.0  | 1890 | 7.5107          | 0.4889   |
| 0.0019        | 36.0  | 1944 | 7.9509          | 0.5111   |
| 0.0807        | 37.0  | 1998 | 8.0204          | 0.4889   |
| 0.0329        | 38.0  | 2052 | 7.6843          | 0.5333   |
| 0.0569        | 39.0  | 2106 | 7.1584          | 0.5111   |
| 0.0005        | 40.0  | 2160 | 7.0397          | 0.4889   |
| 0.0037        | 41.0  | 2214 | 7.3232          | 0.5111   |
| 0.0007        | 42.0  | 2268 | 7.2075          | 0.4889   |
| 0.0001        | 43.0  | 2322 | 7.1929          | 0.5111   |
| 0.0001        | 44.0  | 2376 | 7.3309          | 0.5333   |
| 0.0272        | 45.0  | 2430 | 7.1510          | 0.5333   |
| 0.0499        | 46.0  | 2484 | 7.2579          | 0.5333   |
| 0.0236        | 47.0  | 2538 | 7.2310          | 0.5111   |
| 0.044         | 48.0  | 2592 | 7.1940          | 0.5111   |
| 0.0149        | 49.0  | 2646 | 7.2304          | 0.5111   |
| 0.0068        | 50.0  | 2700 | 7.2304          | 0.5111   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5111111111111111, "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