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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_RMSprop_1e5_20Epoch_Beit-large-224_fold2 |
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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: 0.8523783488244943 |
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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_RMSprop_1e5_20Epoch_Beit-large-224_fold2 |
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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: 1.6527 |
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- Accuracy: 0.8524 |
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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: 1e-05 |
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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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| 0.3607 | 1.0 | 913 | 0.3589 | 0.8565 | |
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| 0.2545 | 2.0 | 1826 | 0.3889 | 0.8537 | |
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| 0.1839 | 3.0 | 2739 | 0.5447 | 0.8455 | |
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| 0.0174 | 4.0 | 3652 | 0.8367 | 0.8548 | |
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| 0.0719 | 5.0 | 4565 | 1.2411 | 0.8428 | |
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| 0.0044 | 6.0 | 5478 | 1.3737 | 0.8425 | |
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| 0.0004 | 7.0 | 6391 | 1.3329 | 0.8529 | |
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| 0.0003 | 8.0 | 7304 | 1.6015 | 0.8477 | |
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| 0.0201 | 9.0 | 8217 | 1.6119 | 0.8491 | |
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| 0.0002 | 10.0 | 9130 | 1.6527 | 0.8524 | |
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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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