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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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- imagefolder |
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metrics: |
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- f1 |
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model-index: |
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- name: Pokemon-classification-1stGen-DataAug |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8973152881701102 |
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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-classification-1stGen-DataAug |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4623 |
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- F1: 0.8973 |
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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: 6.56462271373806e-05 |
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- train_batch_size: 4 |
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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: 16 |
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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: 9 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.525 | 1.0 | 527 | 3.6420 | 0.4635 | |
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| 2.6921 | 2.0 | 1055 | 2.0075 | 0.6360 | |
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| 1.4828 | 3.0 | 1582 | 1.2151 | 0.7582 | |
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| 0.9262 | 4.0 | 2110 | 0.8820 | 0.8297 | |
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| 0.6285 | 5.0 | 2637 | 0.6866 | 0.8734 | |
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| 0.4634 | 6.0 | 3165 | 0.5699 | 0.8854 | |
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| 0.3683 | 7.0 | 3692 | 0.5223 | 0.8913 | |
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| 0.3268 | 8.0 | 4220 | 0.4702 | 0.8967 | |
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| 0.2839 | 8.99 | 4743 | 0.4623 | 0.8973 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.2.0.dev20231126+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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