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# vit-plantnet300k

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the mikehemberger/plantnet300K dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8831
- Accuracy: 0.8046

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 6.2973        | 0.04  | 100  | 2.0799          | 0.6139   |
| 3.413         | 0.08  | 200  | 1.4738          | 0.7076   |
| 2.6718        | 0.12  | 300  | 1.2331          | 0.7479   |
| 2.308         | 0.16  | 400  | 1.0966          | 0.7701   |
| 2.2116        | 0.2   | 500  | 1.0115          | 0.7834   |
| 1.9719        | 0.24  | 600  | 0.9609          | 0.7910   |
| 1.8785        | 0.28  | 700  | 0.9247          | 0.798    |
| 1.7549        | 0.32  | 800  | 0.9014          | 0.8002   |
| 1.8103        | 0.36  | 900  | 0.8874          | 0.8031   |
| 1.7776        | 0.4   | 1000 | 0.8831          | 0.8046   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0

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