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# hushem_5x_beit_base_rms_001_fold4

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: 1.5372
- Accuracy: 0.7619

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4749        | 1.0   | 28   | 1.3999          | 0.2381   |
| 1.39          | 2.0   | 56   | 1.4010          | 0.2619   |
| 1.4057        | 3.0   | 84   | 1.3886          | 0.2381   |
| 1.3953        | 4.0   | 112  | 1.3773          | 0.2381   |
| 1.3855        | 5.0   | 140  | 1.3607          | 0.2619   |
| 1.3721        | 6.0   | 168  | 1.1238          | 0.5      |
| 1.2199        | 7.0   | 196  | 1.2305          | 0.4762   |
| 1.1505        | 8.0   | 224  | 0.9832          | 0.4762   |
| 1.1076        | 9.0   | 252  | 0.9145          | 0.5476   |
| 1.04          | 10.0  | 280  | 0.9689          | 0.5476   |
| 0.9947        | 11.0  | 308  | 0.8866          | 0.6429   |
| 1.0266        | 12.0  | 336  | 0.8639          | 0.6905   |
| 0.9955        | 13.0  | 364  | 0.8959          | 0.6190   |
| 0.9564        | 14.0  | 392  | 0.8608          | 0.6667   |
| 0.9123        | 15.0  | 420  | 0.7711          | 0.6905   |
| 0.9391        | 16.0  | 448  | 0.7070          | 0.7619   |
| 0.9117        | 17.0  | 476  | 0.7366          | 0.7619   |
| 0.902         | 18.0  | 504  | 0.7650          | 0.7143   |
| 0.8479        | 19.0  | 532  | 0.7181          | 0.7381   |
| 0.8138        | 20.0  | 560  | 0.8337          | 0.6667   |
| 0.7593        | 21.0  | 588  | 0.8325          | 0.6905   |
| 0.8558        | 22.0  | 616  | 0.7211          | 0.8095   |
| 0.8609        | 23.0  | 644  | 0.7758          | 0.7619   |
| 0.7997        | 24.0  | 672  | 0.8535          | 0.7143   |
| 0.6915        | 25.0  | 700  | 0.8962          | 0.7381   |
| 0.7445        | 26.0  | 728  | 0.7116          | 0.7619   |
| 0.6818        | 27.0  | 756  | 0.9464          | 0.5714   |
| 0.6812        | 28.0  | 784  | 0.6802          | 0.7143   |
| 0.662         | 29.0  | 812  | 1.0464          | 0.5476   |
| 0.6161        | 30.0  | 840  | 0.7154          | 0.7857   |
| 0.5942        | 31.0  | 868  | 0.6122          | 0.7619   |
| 0.571         | 32.0  | 896  | 0.6263          | 0.7857   |
| 0.5357        | 33.0  | 924  | 0.8564          | 0.8095   |
| 0.4815        | 34.0  | 952  | 0.9986          | 0.7381   |
| 0.5261        | 35.0  | 980  | 0.9173          | 0.8095   |
| 0.3508        | 36.0  | 1008 | 1.0846          | 0.7619   |
| 0.3469        | 37.0  | 1036 | 0.9412          | 0.8333   |
| 0.3024        | 38.0  | 1064 | 0.9602          | 0.8333   |
| 0.2908        | 39.0  | 1092 | 1.1234          | 0.8333   |
| 0.2222        | 40.0  | 1120 | 1.1275          | 0.8095   |
| 0.2149        | 41.0  | 1148 | 1.4618          | 0.7381   |
| 0.2207        | 42.0  | 1176 | 1.3470          | 0.7857   |
| 0.094         | 43.0  | 1204 | 1.5389          | 0.7619   |
| 0.1227        | 44.0  | 1232 | 1.3819          | 0.7857   |
| 0.0713        | 45.0  | 1260 | 1.5287          | 0.7619   |
| 0.0383        | 46.0  | 1288 | 1.5676          | 0.8095   |
| 0.0259        | 47.0  | 1316 | 1.4966          | 0.7857   |
| 0.023         | 48.0  | 1344 | 1.5355          | 0.7619   |
| 0.0304        | 49.0  | 1372 | 1.5372          | 0.7619   |
| 0.0233        | 50.0  | 1400 | 1.5372          | 0.7619   |


### 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_rms_001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7619047619047619, "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