| --- |
| 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 |
| |
