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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-large-patch16-224 |
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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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- accuracy |
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model-index: |
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- name: Boya2_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold1 |
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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: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8595336076817558 |
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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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# Boya2_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold1 |
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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: 1.4832 |
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- Accuracy: 0.8595 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| 0.3205 | 1.0 | 914 | 0.4126 | 0.8335 | |
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| 0.3896 | 2.0 | 1828 | 0.3489 | 0.8595 | |
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| 0.2815 | 3.0 | 2742 | 0.4941 | 0.8250 | |
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| 0.0932 | 4.0 | 3656 | 0.8851 | 0.8431 | |
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| 0.0061 | 5.0 | 4570 | 1.0518 | 0.8527 | |
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| 0.0199 | 6.0 | 5484 | 1.2561 | 0.8529 | |
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| 0.0725 | 7.0 | 6398 | 1.4266 | 0.8565 | |
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| 0.0 | 8.0 | 7312 | 1.4824 | 0.8543 | |
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| 0.0 | 9.0 | 8226 | 1.4678 | 0.8579 | |
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| 0.0 | 10.0 | 9140 | 1.4832 | 0.8595 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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