🍻 cheers
Browse files- README.md +6 -5
- all_results.json +9 -9
- eval_results.json +5 -5
- runs/Mar18_14-26-58_7e4cb5ba27a4/events.out.tfevents.1710772695.7e4cb5ba27a4.347.1 +3 -0
- train_results.json +4 -4
- trainer_state.json +234 -234
README.md
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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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- renovation
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name: Image Classification
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type: image-classification
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dataset:
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name:
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type: renovation
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config: default
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split: validation
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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# vit-base-renovation
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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
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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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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- image-classification
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- generated_from_trainer
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datasets:
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- renovation
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name: Image Classification
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type: image-classification
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dataset:
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name: renovations
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type: renovation
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config: default
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split: validation
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6545454545454545
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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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# vit-base-renovation
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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 renovations dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7622
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- Accuracy: 0.6545
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## Model description
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all_results.json
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runs/Mar18_14-26-58_7e4cb5ba27a4/events.out.tfevents.1710772695.7e4cb5ba27a4.347.1
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