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# hushem_5x_beit_base_sgd_0001_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: 1.3804
- Accuracy: 0.4048

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4632        | 1.0   | 28   | 1.5173          | 0.2143   |
| 1.3741        | 2.0   | 56   | 1.5094          | 0.2381   |
| 1.4021        | 3.0   | 84   | 1.5010          | 0.2381   |
| 1.3681        | 4.0   | 112  | 1.4942          | 0.2381   |
| 1.4122        | 5.0   | 140  | 1.4872          | 0.2381   |
| 1.3657        | 6.0   | 168  | 1.4803          | 0.2619   |
| 1.3993        | 7.0   | 196  | 1.4742          | 0.2619   |
| 1.3652        | 8.0   | 224  | 1.4681          | 0.2619   |
| 1.3615        | 9.0   | 252  | 1.4624          | 0.2619   |
| 1.3492        | 10.0  | 280  | 1.4574          | 0.2619   |
| 1.3205        | 11.0  | 308  | 1.4526          | 0.2619   |
| 1.3552        | 12.0  | 336  | 1.4476          | 0.2619   |
| 1.3393        | 13.0  | 364  | 1.4435          | 0.2619   |
| 1.3397        | 14.0  | 392  | 1.4389          | 0.2619   |
| 1.3561        | 15.0  | 420  | 1.4347          | 0.2619   |
| 1.3361        | 16.0  | 448  | 1.4313          | 0.2619   |
| 1.3287        | 17.0  | 476  | 1.4281          | 0.2857   |
| 1.3138        | 18.0  | 504  | 1.4246          | 0.3095   |
| 1.3241        | 19.0  | 532  | 1.4213          | 0.3095   |
| 1.3033        | 20.0  | 560  | 1.4184          | 0.3095   |
| 1.3163        | 21.0  | 588  | 1.4155          | 0.3095   |
| 1.3116        | 22.0  | 616  | 1.4126          | 0.3095   |
| 1.3228        | 23.0  | 644  | 1.4101          | 0.3095   |
| 1.3214        | 24.0  | 672  | 1.4076          | 0.3333   |
| 1.2818        | 25.0  | 700  | 1.4051          | 0.3333   |
| 1.2948        | 26.0  | 728  | 1.4029          | 0.3333   |
| 1.3231        | 27.0  | 756  | 1.4008          | 0.3333   |
| 1.2969        | 28.0  | 784  | 1.3988          | 0.3333   |
| 1.2659        | 29.0  | 812  | 1.3969          | 0.3333   |
| 1.2426        | 30.0  | 840  | 1.3952          | 0.3571   |
| 1.2934        | 31.0  | 868  | 1.3935          | 0.3810   |
| 1.2777        | 32.0  | 896  | 1.3917          | 0.4048   |
| 1.2767        | 33.0  | 924  | 1.3904          | 0.4048   |
| 1.3162        | 34.0  | 952  | 1.3892          | 0.4048   |
| 1.2726        | 35.0  | 980  | 1.3880          | 0.4048   |
| 1.294         | 36.0  | 1008 | 1.3868          | 0.4048   |
| 1.2554        | 37.0  | 1036 | 1.3858          | 0.4048   |
| 1.2838        | 38.0  | 1064 | 1.3848          | 0.4048   |
| 1.2842        | 39.0  | 1092 | 1.3839          | 0.4048   |
| 1.2721        | 40.0  | 1120 | 1.3832          | 0.4048   |
| 1.2562        | 41.0  | 1148 | 1.3826          | 0.4048   |
| 1.2576        | 42.0  | 1176 | 1.3821          | 0.4048   |
| 1.3           | 43.0  | 1204 | 1.3815          | 0.4048   |
| 1.273         | 44.0  | 1232 | 1.3811          | 0.4048   |
| 1.2913        | 45.0  | 1260 | 1.3808          | 0.4048   |
| 1.2814        | 46.0  | 1288 | 1.3806          | 0.4048   |
| 1.2272        | 47.0  | 1316 | 1.3805          | 0.4048   |
| 1.2516        | 48.0  | 1344 | 1.3804          | 0.4048   |
| 1.2555        | 49.0  | 1372 | 1.3804          | 0.4048   |
| 1.3084        | 50.0  | 1400 | 1.3804          | 0.4048   |


### 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_0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.40476190476190477, "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