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# UL_bedroom_classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1283
- Accuracy: 0.9578

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9730 | 9    | 0.4275          | 0.8464   |
| 0.7101        | 1.9459 | 18   | 0.1990          | 0.9518   |
| 0.3133        | 2.9189 | 27   | 0.1399          | 0.9548   |
| 0.2012        | 4.0    | 37   | 0.1229          | 0.9548   |
| 0.1724        | 4.9730 | 46   | 0.1384          | 0.9488   |
| 0.1458        | 5.9459 | 55   | 0.1240          | 0.9518   |
| 0.1476        | 6.8108 | 63   | 0.1283          | 0.9578   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

bathroom bedroom kitchen