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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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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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- accuracy |
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model-index: |
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- name: croupier-creature-classifier |
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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: croupier-mtg-dataset |
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type: imagefolder |
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config: alkzar90--croupier-mtg-dataset |
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split: train |
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args: alkzar90--croupier-mtg-dataset |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8058823529411765 |
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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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# croupier-creature-classifier |
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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 croupier-mtg-dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6480 |
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- Accuracy: 0.8059 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 0.1967 | 1.1 | 100 | 0.6480 | 0.8059 | |
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| 0.1047 | 2.2 | 200 | 0.8703 | 0.7529 | |
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| 0.2249 | 3.3 | 300 | 0.9539 | 0.7588 | |
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| 0.0984 | 4.4 | 400 | 0.9319 | 0.7529 | |
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| 0.086 | 5.49 | 500 | 0.9061 | 0.7706 | |
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| 0.1164 | 6.59 | 600 | 0.7493 | 0.8176 | |
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| 0.0518 | 7.69 | 700 | 0.8781 | 0.7765 | |
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| 0.0458 | 8.79 | 800 | 0.8851 | 0.7824 | |
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| 0.0521 | 9.89 | 900 | 0.9448 | 0.7882 | |
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| 0.0576 | 10.99 | 1000 | 0.8884 | 0.7824 | |
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| 0.0442 | 12.09 | 1100 | 0.8965 | 0.7882 | |
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| 0.0254 | 13.19 | 1200 | 0.9140 | 0.7882 | |
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| 0.0426 | 14.29 | 1300 | 0.9274 | 0.7882 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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