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# finetuned-vit-flowers

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1365
- Accuracy: 0.9653

## Model description

Entrenamiento apoyado de: https://github.com/huggingface/notebooks/blob/main/examples/image_classification.ipynb

## Intended uses & limitations

Proyecto final

## Training and evaluation data

https://huggingface.co/datasets/DeadPixels/DPhi_Sprint_25_Flowers

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1236        | 0.99  | 36   | 0.1509          | 0.9730   |
| 0.1043        | 2.0   | 73   | 0.1235          | 0.9730   |
| 0.1077        | 2.96  | 108  | 0.1365          | 0.9653   |


### 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"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "finetuned-vit-flowers", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us