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# vit-base-oxford-flowers-102

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the Multimodal-Fatima/OxfordFlowers_test_facebook_opt_1.3b_Visclues_ns_6149 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0540
- Accuracy: 0.9951

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3164        | 1.0   | 308  | 0.1577          | 0.9919   |
| 0.0703        | 2.0   | 616  | 0.0557          | 0.9951   |
| 0.0416        | 3.0   | 924  | 0.0417          | 0.9967   |
| 0.0297        | 4.0   | 1232 | 0.0369          | 0.9967   |
| 0.0286        | 5.0   | 1540 | 0.0358          | 0.9967   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1

### Zero-shot classification results
Accuracy: 0.7214
Precision: 0.7092
Recall: 0.7214

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