End of training
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- pytorch_model.bin +1 -1
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 [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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## Model description
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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:
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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.
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| 0.
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| 0.0083 | 6.0 | 3786 | 1.5038 | 0.8239 |
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| 0.0374 | 7.0 | 4417 | 1.6141 | 0.8326 |
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| 0.0 | 8.0 | 5048 | 1.6544 | 0.8259 |
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| 0.0 | 9.0 | 5679 | 1.7031 | 0.8338 |
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| 0.0001 | 10.0 | 6310 | 1.7149 | 0.8326 |
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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: 0.8310303987366758
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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 [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1668
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- Accuracy: 0.8310
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## Model description
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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: 5
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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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| 0.5068 | 1.0 | 631 | 0.4278 | 0.8291 |
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| 0.3715 | 2.0 | 1262 | 0.4212 | 0.8235 |
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| 0.1578 | 3.0 | 1893 | 0.4810 | 0.8354 |
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| 0.0708 | 4.0 | 2524 | 0.9491 | 0.8251 |
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| 0.1011 | 5.0 | 3155 | 1.1668 | 0.8310 |
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### Framework versions
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pytorch_model.bin
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