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--- |
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license: apache-2.0 |
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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: weather-base |
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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: dataset |
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split: train |
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args: dataset |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9358600583090378 |
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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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# weather-base |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2184 |
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- Accuracy: 0.9359 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 6 |
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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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| 0.3368 | 1.0 | 171 | 0.2780 | 0.9009 | |
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| 0.2129 | 2.0 | 342 | 0.2333 | 0.9300 | |
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| 0.1827 | 3.0 | 513 | 0.2440 | 0.9213 | |
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| 0.1475 | 4.0 | 684 | 0.2306 | 0.9315 | |
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| 0.1284 | 5.0 | 855 | 0.2192 | 0.9359 | |
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| 0.0526 | 6.0 | 1026 | 0.2184 | 0.9359 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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