Librarian Bot: Add base_model information to model
#2
by
librarian-bot
- opened
README.md
CHANGED
@@ -5,6 +5,8 @@ tags:
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datasets:
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- image_folder
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- nielsr/eurosat-demo
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widget:
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- src: https://drive.google.com/uc?id=1trKgvkMRQ3BB0VcqnDwmieLxXhWmS8rq
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example_title: Annual Crop
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@@ -26,22 +28,21 @@ widget:
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example_title: River
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- src: https://drive.google.com/uc?id=1zVAfR7N5hXy6eq1cVOd8bXPjC1sqxVir
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example_title: Sea Lake
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- accuracy
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model-index:
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- name: swin-tiny-patch4-window7-224-finetuned-eurosat
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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: image_folder
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type: image_folder
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args: default
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metrics:
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-
-
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type: accuracy
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value: 0.9848148148148148
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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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datasets:
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- image_folder
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- nielsr/eurosat-demo
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metrics:
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- accuracy
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widget:
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- src: https://drive.google.com/uc?id=1trKgvkMRQ3BB0VcqnDwmieLxXhWmS8rq
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example_title: Annual Crop
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example_title: River
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- src: https://drive.google.com/uc?id=1zVAfR7N5hXy6eq1cVOd8bXPjC1sqxVir
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example_title: Sea Lake
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base_model: microsoft/swin-tiny-patch4-window7-224
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model-index:
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- name: swin-tiny-patch4-window7-224-finetuned-eurosat
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results:
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- task:
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type: image-classification
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name: Image Classification
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dataset:
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name: image_folder
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type: image_folder
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args: default
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metrics:
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- type: accuracy
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value: 0.9848148148148148
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name: Accuracy
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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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