rshrott commited on
Commit
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Model save

Browse files
README.md CHANGED
@@ -2,7 +2,6 @@
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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
@@ -15,7 +14,7 @@ model-index:
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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: renovation
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  config: default
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  split: validation
@@ -23,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.6575342465753424
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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
@@ -31,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-base-beans-demo-v5
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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: 0.7925
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- - Accuracy: 0.6575
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  ## Model description
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@@ -66,10 +65,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.1711 | 0.81 | 100 | 1.0255 | 0.5982 |
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- | 0.7083 | 1.61 | 200 | 0.7925 | 0.6575 |
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- | 0.2479 | 2.42 | 300 | 0.8712 | 0.6941 |
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- | 0.127 | 3.23 | 400 | 0.8440 | 0.6941 |
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  ### Framework versions
 
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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: renovation
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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: 0.6986301369863014
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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-beans-demo-v5
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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 renovation dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0644
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+ - Accuracy: 0.6986
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6438 | 0.81 | 100 | 0.9295 | 0.6347 |
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+ | 0.3105 | 1.61 | 200 | 0.9350 | 0.6575 |
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+ | 0.0634 | 2.42 | 300 | 1.0782 | 0.6895 |
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+ | 0.0257 | 3.23 | 400 | 1.0644 | 0.6986 |
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  ### Framework versions
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