---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: fish_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9969230769230769
    - name: F1
      type: f1
      value: 0.9970182569296375
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# fish_classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2213
- Accuracy: 0.9969
- F1: 0.9970

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.5189        | 1.0   | 71   | 1.0828          | 0.9969   | 0.9970 |
| 0.7083        | 2.0   | 142  | 0.5398          | 0.9954   | 0.9955 |
| 0.3727        | 3.0   | 213  | 0.3473          | 0.9954   | 0.9955 |
| 0.2624        | 4.0   | 284  | 0.2734          | 0.9985   | 0.9985 |
| 0.2184        | 5.0   | 355  | 0.2401          | 0.9985   | 0.9985 |
| 0.1972        | 6.0   | 426  | 0.2238          | 0.9985   | 0.9985 |
| 0.1879        | 7.0   | 497  | 0.2213          | 0.9969   | 0.9970 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2