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# hushem_40x_beit_large_sgd_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: 1.1143
- Accuracy: 0.7333

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9697        | 1.0   | 429   | 1.2154          | 0.4667   |
| 0.6115        | 2.0   | 858   | 1.0239          | 0.6      |
| 0.4295        | 3.0   | 1287  | 0.8687          | 0.6667   |
| 0.3148        | 4.0   | 1716  | 0.7911          | 0.6667   |
| 0.2073        | 5.0   | 2145  | 0.7767          | 0.6667   |
| 0.1701        | 6.0   | 2574  | 0.7537          | 0.7111   |
| 0.1083        | 7.0   | 3003  | 0.7426          | 0.6667   |
| 0.1019        | 8.0   | 3432  | 0.7724          | 0.6667   |
| 0.0731        | 9.0   | 3861  | 0.8002          | 0.6667   |
| 0.0641        | 10.0  | 4290  | 0.8057          | 0.6889   |
| 0.0475        | 11.0  | 4719  | 0.8186          | 0.6889   |
| 0.0374        | 12.0  | 5148  | 0.8455          | 0.6889   |
| 0.036         | 13.0  | 5577  | 0.8659          | 0.6889   |
| 0.0356        | 14.0  | 6006  | 0.8691          | 0.6889   |
| 0.0264        | 15.0  | 6435  | 0.8888          | 0.6889   |
| 0.0165        | 16.0  | 6864  | 0.9285          | 0.6889   |
| 0.0197        | 17.0  | 7293  | 0.9269          | 0.6889   |
| 0.015         | 18.0  | 7722  | 0.9244          | 0.6889   |
| 0.0084        | 19.0  | 8151  | 0.9294          | 0.7111   |
| 0.0209        | 20.0  | 8580  | 0.9610          | 0.6889   |
| 0.0077        | 21.0  | 9009  | 0.9885          | 0.6889   |
| 0.0098        | 22.0  | 9438  | 1.0003          | 0.7111   |
| 0.0055        | 23.0  | 9867  | 0.9875          | 0.7111   |
| 0.0097        | 24.0  | 10296 | 0.9869          | 0.7111   |
| 0.0191        | 25.0  | 10725 | 1.0265          | 0.6889   |
| 0.0148        | 26.0  | 11154 | 1.0066          | 0.7111   |
| 0.0075        | 27.0  | 11583 | 1.0339          | 0.7111   |
| 0.0033        | 28.0  | 12012 | 1.0184          | 0.7111   |
| 0.0046        | 29.0  | 12441 | 1.0436          | 0.7111   |
| 0.0053        | 30.0  | 12870 | 1.0585          | 0.7111   |
| 0.0014        | 31.0  | 13299 | 1.0507          | 0.7111   |
| 0.0049        | 32.0  | 13728 | 1.0621          | 0.7111   |
| 0.004         | 33.0  | 14157 | 1.0547          | 0.7111   |
| 0.0022        | 34.0  | 14586 | 1.0799          | 0.7111   |
| 0.0039        | 35.0  | 15015 | 1.1016          | 0.7111   |
| 0.0052        | 36.0  | 15444 | 1.1070          | 0.7111   |
| 0.0029        | 37.0  | 15873 | 1.1084          | 0.7111   |
| 0.0056        | 38.0  | 16302 | 1.0729          | 0.7111   |
| 0.0081        | 39.0  | 16731 | 1.0978          | 0.7333   |
| 0.0009        | 40.0  | 17160 | 1.1093          | 0.7333   |
| 0.0041        | 41.0  | 17589 | 1.0986          | 0.7333   |
| 0.0028        | 42.0  | 18018 | 1.1077          | 0.7333   |
| 0.0017        | 43.0  | 18447 | 1.1073          | 0.7111   |
| 0.0014        | 44.0  | 18876 | 1.1103          | 0.7333   |
| 0.0126        | 45.0  | 19305 | 1.1061          | 0.7333   |
| 0.005         | 46.0  | 19734 | 1.1183          | 0.7333   |
| 0.0044        | 47.0  | 20163 | 1.1159          | 0.7333   |
| 0.0041        | 48.0  | 20592 | 1.1141          | 0.7333   |
| 0.0008        | 49.0  | 21021 | 1.1138          | 0.7333   |
| 0.014         | 50.0  | 21450 | 1.1143          | 0.7333   |


### 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_40x_beit_large_sgd_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": 0.7333333333333333, "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