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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pokemon-classification |
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metrics: |
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- accuracy |
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model-index: |
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- name: pokemon_class_model |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: pokemon-classification |
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type: pokemon-classification |
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config: full |
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split: train |
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args: full |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8439425051334702 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# pokemon_class_model |
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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 pokemon-classification dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7799 |
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- Accuracy: 0.8439 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 4.871 | 1.0 | 61 | 4.8286 | 0.1129 | |
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| 4.4362 | 2.0 | 122 | 4.3949 | 0.5626 | |
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| 3.9543 | 3.0 | 183 | 3.9551 | 0.7238 | |
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| 3.5859 | 4.0 | 244 | 3.6081 | 0.7772 | |
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| 3.2793 | 5.0 | 305 | 3.3454 | 0.8049 | |
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| 3.0146 | 6.0 | 366 | 3.1411 | 0.8152 | |
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| 2.8492 | 7.0 | 427 | 2.9854 | 0.8347 | |
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| 2.6706 | 8.0 | 488 | 2.8625 | 0.8501 | |
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| 2.5676 | 9.0 | 549 | 2.8014 | 0.8337 | |
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| 2.6059 | 10.0 | 610 | 2.7799 | 0.8439 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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