| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: pokemon_classification |
| | 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. --> |
| |
|
| | # pokemon_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 None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.0586 |
| | - Accuracy: 0.9071 |
| | |
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 8 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 4.3925 | 1.0 | 350 | 4.0653 | 0.6705 | |
| | | 3.2005 | 2.0 | 700 | 3.1602 | 0.8227 | |
| | | 2.3615 | 3.0 | 1050 | 2.4281 | 0.8656 | |
| | | 1.5369 | 4.0 | 1400 | 1.8786 | 0.8821 | |
| | | 1.0741 | 5.0 | 1750 | 1.4818 | 0.9014 | |
| | | 0.7094 | 6.0 | 2100 | 1.2335 | 0.9014 | |
| | | 0.544 | 7.0 | 2450 | 1.0976 | 0.9042 | |
| | | 0.4622 | 8.0 | 2800 | 1.0586 | 0.9071 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.34.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.0 |
| | |
