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# Accomodation_room_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: 0.3910
- Accuracy: 0.875

## 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        | 1.0   | 5    | 0.6710          | 0.8182   |
| 0.5771        | 2.0   | 10   | 0.5322          | 0.8523   |
| 0.5771        | 3.0   | 15   | 0.4599          | 0.8580   |
| 0.3947        | 4.0   | 20   | 0.4182          | 0.8636   |
| 0.3947        | 5.0   | 25   | 0.3910          | 0.875    |
| 0.3635        | 6.0   | 30   | 0.3867          | 0.875    |
| 0.3635        | 7.0   | 35   | 0.3858          | 0.8580   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

amenities bathroom bedroom exterior floor_plan kitchen living_room others