| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: Birdsclassification |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # Birdsclassification |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3057 |
| - Accuracy: 0.9307 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 256 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 16 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 5.42 | 1.0 | 262 | 3.6698 | 0.7571 | |
| | 1.7968 | 2.0 | 525 | 0.9179 | 0.8396 | |
| | 0.6598 | 3.0 | 787 | 0.6370 | 0.8654 | |
| | 0.4867 | 4.0 | 1050 | 0.5493 | 0.8765 | |
| | 0.4055 | 5.0 | 1312 | 0.5093 | 0.8833 | |
| | 0.3513 | 6.0 | 1575 | 0.4602 | 0.8892 | |
| | 0.3053 | 7.0 | 1837 | 0.4350 | 0.8977 | |
| | 0.2692 | 8.0 | 2100 | 0.4130 | 0.9021 | |
| | 0.2446 | 9.0 | 2362 | 0.4218 | 0.9018 | |
| | 0.2267 | 10.0 | 2625 | 0.3667 | 0.9130 | |
| | 0.2018 | 11.0 | 2887 | 0.3632 | 0.9154 | |
| | 0.1842 | 12.0 | 3150 | 0.3533 | 0.9154 | |
| | 0.1636 | 13.0 | 3412 | 0.3396 | 0.9206 | |
| | 0.1511 | 14.0 | 3675 | 0.3125 | 0.9266 | |
| | 0.1411 | 15.0 | 3937 | 0.2833 | 0.9329 | |
| | 0.1259 | 15.97 | 4192 | 0.3057 | 0.9307 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
