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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: Boya1_3Class_SGD_1e3_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: 0.7360847135487374 |
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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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# Boya1_3Class_SGD_1e3_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: 0.6426 |
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- Accuracy: 0.7361 |
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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: 0.001 |
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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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| 0.8408 | 1.0 | 924 | 0.9037 | 0.6155 | |
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| 0.8244 | 2.0 | 1848 | 0.7895 | 0.6715 | |
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| 0.8238 | 3.0 | 2772 | 0.7327 | 0.6951 | |
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| 0.6266 | 4.0 | 3696 | 0.6993 | 0.7092 | |
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| 0.7355 | 5.0 | 4620 | 0.6767 | 0.7220 | |
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| 0.6356 | 6.0 | 5544 | 0.6627 | 0.7288 | |
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| 0.6111 | 7.0 | 6468 | 0.6531 | 0.7317 | |
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| 0.6432 | 8.0 | 7392 | 0.6463 | 0.7355 | |
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| 0.5597 | 9.0 | 8316 | 0.6435 | 0.7353 | |
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| 0.7957 | 10.0 | 9240 | 0.6426 | 0.7361 | |
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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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