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# city_multiclass_classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2000
- Accuracy: 0.9667

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6756        | 1.0   | 53   | 1.2548          | 0.8389   |
| 0.3699        | 2.0   | 106  | 0.3864          | 0.9667   |
| 0.0426        | 3.0   | 159  | 0.1737          | 0.9889   |
| 0.0101        | 4.0   | 212  | 0.1243          | 0.9889   |
| 0.0062        | 5.0   | 265  | 0.1115          | 0.9889   |
| 0.0046        | 6.0   | 318  | 0.1028          | 0.9889   |
| 0.0037        | 7.0   | 371  | 0.0979          | 0.9889   |
| 0.0034        | 8.0   | 424  | 0.0928          | 0.9889   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7 label_8 label_9 label_10 label_11 label_12 label_13 label_14 label_15 label_16 label_17 label_18 label_19 label_20 label_21 label_22 label_23 label_24 label_25 label_26 label_27 label_28 label_29