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# dogv2

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.8333
- F1: 0.8207
- Precision: 0.8639
- Recall: 0.8333
- Loss: 2.0509

## 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: 0.0004
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Precision | Recall | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:---------------:|
| 0.1691        | 1.0   | 46   | 0.75     | 0.7406 | 0.7505    | 0.75   | 1.5006          |
| 0.0862        | 2.0   | 92   | 0.8333   | 0.8207 | 0.8639    | 0.8333 | 2.0509          |
| 0.0973        | 3.0   | 138  | 0.7667   | 0.7417 | 0.8241    | 0.7667 | 2.0640          |
| 0.1052        | 4.0   | 184  | 0.8333   | 0.8252 | 0.8475    | 0.8333 | 1.3136          |
| 0.0753        | 5.0   | 230  | 0.8      | 0.7794 | 0.8457    | 0.8000 | 1.9327          |
| 0.0769        | 6.0   | 276  | 0.8      | 0.7877 | 0.8474    | 0.8000 | 2.0386          |
| 0.0978        | 7.0   | 322  | 0.8      | 0.7794 | 0.8457    | 0.8000 | 1.7489          |
| 0.1156        | 8.0   | 368  | 0.8333   | 0.8244 | 0.8471    | 0.8333 | 1.0451          |
| 0.0921        | 9.0   | 414  | 0.7667   | 0.7363 | 0.8343    | 0.7667 | 2.0946          |
| 0.0986        | 10.0  | 460  | 0.7333   | 0.6938 | 0.8051    | 0.7333 | 2.8476          |


### 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", "f1", "precision", "recall"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "dogv2", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us