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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: Boya3_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold4 |
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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: 0.8427722772277227 |
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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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# Boya3_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold4 |
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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: 1.6371 |
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- Accuracy: 0.8428 |
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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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| 0.387 | 1.0 | 632 | 0.4262 | 0.8313 | |
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| 0.2307 | 2.0 | 1264 | 0.4759 | 0.7952 | |
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| 0.175 | 3.0 | 1896 | 0.5470 | 0.8238 | |
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| 0.0757 | 4.0 | 2528 | 0.8287 | 0.8388 | |
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| 0.0394 | 5.0 | 3160 | 1.0981 | 0.8451 | |
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| 0.0241 | 6.0 | 3792 | 1.2962 | 0.8285 | |
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| 0.0403 | 7.0 | 4424 | 1.4716 | 0.8325 | |
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| 0.0001 | 8.0 | 5056 | 1.5920 | 0.8436 | |
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| 0.0035 | 9.0 | 5688 | 1.6035 | 0.8384 | |
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| 0.0 | 10.0 | 6320 | 1.6371 | 0.8428 | |
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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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