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# vit-base-patch16-224-finetuned-algae-rgb

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: 1.0685
- Accuracy: 0.6174

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.981         | 1.0   | 120  | 1.0513          | 0.5698   |
| 1.0027        | 2.0   | 240  | 1.0316          | 0.5775   |
| 0.9554        | 3.0   | 360  | 0.9944          | 0.5945   |
| 0.978         | 4.0   | 480  | 0.9735          | 0.5980   |
| 0.8983        | 5.0   | 600  | 0.9690          | 0.6033   |
| 0.8561        | 6.0   | 720  | 0.9714          | 0.5968   |
| 0.8438        | 7.0   | 840  | 0.9833          | 0.6039   |
| 0.808         | 8.0   | 960  | 0.9827          | 0.6138   |
| 0.7882        | 9.0   | 1080 | 0.9971          | 0.5962   |
| 0.7422        | 10.0  | 1200 | 0.9901          | 0.6080   |
| 0.7797        | 11.0  | 1320 | 1.0096          | 0.5921   |
| 0.7167        | 12.0  | 1440 | 1.0252          | 0.6092   |
| 0.7445        | 13.0  | 1560 | 1.0364          | 0.6074   |
| 0.6641        | 14.0  | 1680 | 1.0471          | 0.6092   |
| 0.6847        | 15.0  | 1800 | 1.0693          | 0.6138   |
| 0.6418        | 16.0  | 1920 | 1.0685          | 0.6174   |
| 0.6423        | 17.0  | 2040 | 1.0683          | 0.6127   |
| 0.6432        | 18.0  | 2160 | 1.0729          | 0.6127   |
| 0.6208        | 19.0  | 2280 | 1.0801          | 0.6138   |
| 0.588         | 20.0  | 2400 | 1.0802          | 0.6103   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

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