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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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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: beans_image_classification |
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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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config: default |
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split: train[:500] |
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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: 0.96 |
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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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# beans_image_classification |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1072 |
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- Accuracy: 0.96 |
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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: 12 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 48 |
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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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| No log | 0.94 | 8 | 1.3666 | 0.66 | |
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| 0.3651 | 2.0 | 17 | 0.3823 | 0.84 | |
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| 0.5622 | 2.94 | 25 | 0.3333 | 0.86 | |
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| 0.3373 | 4.0 | 34 | 0.1274 | 0.97 | |
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| 0.2055 | 4.94 | 42 | 0.1882 | 0.93 | |
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| 0.1819 | 6.0 | 51 | 0.2265 | 0.9 | |
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| 0.1819 | 6.94 | 59 | 0.2395 | 0.91 | |
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| 0.2428 | 8.0 | 68 | 0.1451 | 0.97 | |
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| 0.1305 | 8.94 | 76 | 0.1554 | 0.94 | |
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| 0.1203 | 9.41 | 80 | 0.1705 | 0.92 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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