Model save
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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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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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size:
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.2753 | 2.22 | 600 | 0.5251 | 0.8444 |
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| 0.2569 | 2.59 | 700 | 0.5792 | 0.8259 |
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| 0.2251 | 2.96 | 800 | 0.4169 | 0.8731 |
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| 0.086 | 3.33 | 900 | 0.4182 | 0.8843 |
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| 0.1352 | 3.7 | 1000 | 0.3711 | 0.8880 |
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| 0.0608 | 4.07 | 1100 | 0.3430 | 0.9046 |
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| 0.0175 | 4.44 | 1200 | 0.3241 | 0.9185 |
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| 0.0149 | 4.81 | 1300 | 0.3224 | 0.9102 |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8814814814814815
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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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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: 0.5871
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- Accuracy: 0.8815
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## Model description
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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: 4
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.9351 | 0.93 | 1000 | 0.8621 | 0.7194 |
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| 0.6665 | 1.85 | 2000 | 0.7748 | 0.7880 |
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| 0.0161 | 2.78 | 3000 | 0.6623 | 0.8481 |
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| 0.0069 | 3.7 | 4000 | 0.6439 | 0.8583 |
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| 0.0071 | 4.63 | 5000 | 0.5871 | 0.8815 |
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### Framework versions
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runs/Mar18_08-24-00_cd2d1c1da590/events.out.tfevents.1710750255.cd2d1c1da590.4304.1
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