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# hushem_5x_beit_base_rms_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: 1.4768
- Accuracy: 0.6279

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.51          | 1.0   | 28   | 1.6351          | 0.2558   |
| 1.3869        | 2.0   | 56   | 1.4127          | 0.2558   |
| 1.3848        | 3.0   | 84   | 1.3895          | 0.2558   |
| 1.4113        | 4.0   | 112  | 1.3824          | 0.2558   |
| 1.3569        | 5.0   | 140  | 1.4121          | 0.2326   |
| 1.4625        | 6.0   | 168  | 1.3739          | 0.2326   |
| 1.3804        | 7.0   | 196  | 1.2185          | 0.5349   |
| 1.1352        | 8.0   | 224  | 1.1411          | 0.4884   |
| 1.0899        | 9.0   | 252  | 1.2426          | 0.3953   |
| 1.0945        | 10.0  | 280  | 1.1820          | 0.3488   |
| 1.1149        | 11.0  | 308  | 1.4574          | 0.3023   |
| 0.9942        | 12.0  | 336  | 1.4728          | 0.3256   |
| 1.0204        | 13.0  | 364  | 0.9801          | 0.5581   |
| 0.9987        | 14.0  | 392  | 1.0096          | 0.5349   |
| 1.0664        | 15.0  | 420  | 1.0007          | 0.5814   |
| 0.9463        | 16.0  | 448  | 1.2188          | 0.3953   |
| 0.9756        | 17.0  | 476  | 1.1284          | 0.5116   |
| 0.9698        | 18.0  | 504  | 1.4394          | 0.4419   |
| 1.061         | 19.0  | 532  | 1.1162          | 0.4884   |
| 0.8426        | 20.0  | 560  | 1.9296          | 0.3721   |
| 0.876         | 21.0  | 588  | 1.0070          | 0.5581   |
| 0.8908        | 22.0  | 616  | 1.2196          | 0.5349   |
| 0.8599        | 23.0  | 644  | 0.9502          | 0.6047   |
| 0.8338        | 24.0  | 672  | 0.8737          | 0.6279   |
| 0.785         | 25.0  | 700  | 1.1006          | 0.5814   |
| 0.82          | 26.0  | 728  | 1.0398          | 0.5814   |
| 0.8016        | 27.0  | 756  | 1.6671          | 0.3256   |
| 0.8574        | 28.0  | 784  | 1.1704          | 0.6279   |
| 0.8104        | 29.0  | 812  | 1.0502          | 0.6279   |
| 0.7421        | 30.0  | 840  | 0.9270          | 0.5814   |
| 0.7093        | 31.0  | 868  | 1.8057          | 0.4186   |
| 0.7469        | 32.0  | 896  | 0.9665          | 0.5814   |
| 0.7175        | 33.0  | 924  | 0.8190          | 0.6512   |
| 0.7129        | 34.0  | 952  | 1.0680          | 0.6279   |
| 0.7793        | 35.0  | 980  | 1.0966          | 0.5581   |
| 0.6879        | 36.0  | 1008 | 0.9990          | 0.5814   |
| 0.7016        | 37.0  | 1036 | 1.7556          | 0.4884   |
| 0.6238        | 38.0  | 1064 | 1.5792          | 0.4651   |
| 0.6025        | 39.0  | 1092 | 1.1502          | 0.6047   |
| 0.7264        | 40.0  | 1120 | 1.3317          | 0.5349   |
| 0.6063        | 41.0  | 1148 | 1.5492          | 0.5116   |
| 0.5816        | 42.0  | 1176 | 1.5787          | 0.5814   |
| 0.4627        | 43.0  | 1204 | 1.1301          | 0.6047   |
| 0.4652        | 44.0  | 1232 | 1.5008          | 0.6279   |
| 0.3885        | 45.0  | 1260 | 1.3167          | 0.6279   |
| 0.4003        | 46.0  | 1288 | 1.3851          | 0.6512   |
| 0.3882        | 47.0  | 1316 | 1.4601          | 0.6047   |
| 0.353         | 48.0  | 1344 | 1.4699          | 0.6279   |
| 0.3487        | 49.0  | 1372 | 1.4768          | 0.6279   |
| 0.2789        | 50.0  | 1400 | 1.4768          | 0.6279   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.627906976744186, "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