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README.md
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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.
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- Accuracy: 0.
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## Model description
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- seed: 42
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- distributed_type: IPU
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- gradient_accumulation_steps: 32
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- total_train_batch_size:
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- total_eval_batch_size:
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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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: 0.0548
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- Accuracy: 0.9893
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## Model description
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- seed: 42
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- distributed_type: IPU
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- gradient_accumulation_steps: 32
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- total_train_batch_size: 32
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- total_eval_batch_size: 4
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.1182 | 1.0 | 759 | 0.1451 | 0.9752 |
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| 0.132 | 2.0 | 1518 | 0.0755 | 0.9841 |
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| 0.0262 | 3.0 | 2277 | 0.0548 | 0.9893 |
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### Framework versions
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