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--- |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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datasets: |
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- beans |
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metrics: |
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- accuracy |
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model-index: |
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- name: resnet-50-base-beans-demo |
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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: beans |
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type: beans |
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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: 0.9699248120300752 |
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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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# resnet-50-base-beans-demo |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the beans dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1014 |
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- Accuracy: 0.9699 |
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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: 0.002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5.0 |
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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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| 0.9524 | 1.0 | 130 | 0.2826 | 0.8647 | |
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| 0.3596 | 2.0 | 260 | 0.2216 | 0.9023 | |
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| 0.2419 | 3.0 | 390 | 0.1324 | 0.9474 | |
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| 0.3248 | 4.0 | 520 | 0.1124 | 0.9699 | |
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| 0.1557 | 5.0 | 650 | 0.1014 | 0.9699 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.2.1 |
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- Tokenizers 0.12.1 |
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