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# hushem_5x_beit_base_sgd_001_fold3

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0930
- Accuracy: 0.5814

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5405        | 1.0   | 28   | 1.5276          | 0.2791   |
| 1.4164        | 2.0   | 56   | 1.4818          | 0.2558   |
| 1.3492        | 3.0   | 84   | 1.4545          | 0.3023   |
| 1.3001        | 4.0   | 112  | 1.4313          | 0.3256   |
| 1.2739        | 5.0   | 140  | 1.4088          | 0.3256   |
| 1.2528        | 6.0   | 168  | 1.3949          | 0.3488   |
| 1.2748        | 7.0   | 196  | 1.3862          | 0.3953   |
| 1.2477        | 8.0   | 224  | 1.3731          | 0.3953   |
| 1.1334        | 9.0   | 252  | 1.3517          | 0.4419   |
| 1.2313        | 10.0  | 280  | 1.3394          | 0.4419   |
| 1.1559        | 11.0  | 308  | 1.3288          | 0.4651   |
| 1.1429        | 12.0  | 336  | 1.3194          | 0.4884   |
| 1.1222        | 13.0  | 364  | 1.3129          | 0.4884   |
| 1.1193        | 14.0  | 392  | 1.3031          | 0.4884   |
| 1.1208        | 15.0  | 420  | 1.2891          | 0.4884   |
| 1.0856        | 16.0  | 448  | 1.2837          | 0.5116   |
| 1.0813        | 17.0  | 476  | 1.2664          | 0.4884   |
| 1.0315        | 18.0  | 504  | 1.2593          | 0.5116   |
| 1.0461        | 19.0  | 532  | 1.2499          | 0.5349   |
| 1.0           | 20.0  | 560  | 1.2343          | 0.5349   |
| 1.0154        | 21.0  | 588  | 1.2288          | 0.5581   |
| 1.0308        | 22.0  | 616  | 1.2111          | 0.5116   |
| 0.9899        | 23.0  | 644  | 1.2091          | 0.5349   |
| 0.9581        | 24.0  | 672  | 1.2017          | 0.4651   |
| 0.9805        | 25.0  | 700  | 1.1984          | 0.5116   |
| 0.9484        | 26.0  | 728  | 1.1851          | 0.5116   |
| 0.9269        | 27.0  | 756  | 1.1745          | 0.5116   |
| 0.9482        | 28.0  | 784  | 1.1663          | 0.5581   |
| 0.9417        | 29.0  | 812  | 1.1640          | 0.5116   |
| 0.8927        | 30.0  | 840  | 1.1540          | 0.5349   |
| 0.9018        | 31.0  | 868  | 1.1499          | 0.5349   |
| 0.9337        | 32.0  | 896  | 1.1514          | 0.5116   |
| 0.8897        | 33.0  | 924  | 1.1407          | 0.5349   |
| 0.9018        | 34.0  | 952  | 1.1332          | 0.5349   |
| 0.9545        | 35.0  | 980  | 1.1289          | 0.5581   |
| 0.8798        | 36.0  | 1008 | 1.1231          | 0.5581   |
| 0.8701        | 37.0  | 1036 | 1.1207          | 0.5349   |
| 0.8661        | 38.0  | 1064 | 1.1127          | 0.5581   |
| 0.8977        | 39.0  | 1092 | 1.1103          | 0.5349   |
| 0.9369        | 40.0  | 1120 | 1.1062          | 0.5814   |
| 0.8919        | 41.0  | 1148 | 1.1024          | 0.5814   |
| 0.8962        | 42.0  | 1176 | 1.0983          | 0.5814   |
| 0.8751        | 43.0  | 1204 | 1.0966          | 0.5814   |
| 0.895         | 44.0  | 1232 | 1.0957          | 0.5814   |
| 0.863         | 45.0  | 1260 | 1.0942          | 0.5814   |
| 0.8655        | 46.0  | 1288 | 1.0940          | 0.5814   |
| 0.8681        | 47.0  | 1316 | 1.0932          | 0.5814   |
| 0.8242        | 48.0  | 1344 | 1.0930          | 0.5814   |
| 0.8859        | 49.0  | 1372 | 1.0930          | 0.5814   |
| 0.8974        | 50.0  | 1400 | 1.0930          | 0.5814   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_sgd_001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5813953488372093, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us