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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: vit-finetuned-beans |
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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 |
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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: 0.9711538461538461 |
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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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# vit-finetuned-beans |
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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: 0.1157 |
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- Accuracy: 0.9712 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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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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| 0.193 | 1.0 | 117 | 0.1099 | 0.9808 | |
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| 0.0462 | 2.0 | 234 | 0.0857 | 0.9808 | |
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| 0.0171 | 3.0 | 351 | 0.1237 | 0.9712 | |
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| 0.0123 | 4.0 | 468 | 0.1088 | 0.9712 | |
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| 0.0095 | 5.0 | 585 | 0.1135 | 0.9712 | |
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| 0.0081 | 6.0 | 702 | 0.1162 | 0.9712 | |
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| 0.0073 | 7.0 | 819 | 0.1158 | 0.9712 | |
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| 0.0066 | 8.0 | 936 | 0.1152 | 0.9712 | |
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| 0.0061 | 9.0 | 1053 | 0.1160 | 0.9712 | |
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| 0.0061 | 10.0 | 1170 | 0.1157 | 0.9712 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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