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Isaskar
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dinov2-base-finetuned-eurosat

Image Classification
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dinov2
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  1. README.md +16 -11
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@@ -7,6 +7,7 @@ datasets:
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  - imagefolder
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  metrics:
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  - accuracy
 
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  model-index:
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  - name: dinov2-base-finetuned-eurosat
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  results:
@@ -17,12 +18,15 @@ model-index:
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  name: imagefolder
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  type: imagefolder
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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: 0.7536231884057971
 
 
 
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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
@@ -32,8 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5223
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- - Accuracy: 0.7536
 
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  ## Model description
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@@ -65,16 +70,16 @@ The following hyperparameters were used during training:
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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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- | 0.5271 | 0.9960 | 63 | 0.5549 | 0.7135 |
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- | 0.4804 | 1.9921 | 126 | 0.5335 | 0.7380 |
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- | 0.3901 | 2.9881 | 189 | 0.5223 | 0.7536 |
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  ### Framework versions
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- - Transformers 4.40.0
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  - Pytorch 2.2.1+cu121
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- - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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  - imagefolder
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  metrics:
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  - accuracy
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+ - f1
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  model-index:
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  - name: dinov2-base-finetuned-eurosat
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  results:
 
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  name: imagefolder
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  type: imagefolder
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  config: default
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+ split: test
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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: 0.6434627398482821
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+ - name: F1
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+ type: f1
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+ value: 0.12486308871851039
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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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  This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6268
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+ - Accuracy: 0.6435
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+ - F1: 0.1249
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6886 | 0.9858 | 52 | 0.6667 | 0.6189 | 0.0116 |
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+ | 0.6478 | 1.9905 | 105 | 0.6519 | 0.6412 | 0.0 |
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+ | 0.6526 | 2.9573 | 156 | 0.6268 | 0.6435 | 0.1249 |
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  ### Framework versions
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+ - Transformers 4.40.2
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  - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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  - Tokenizers 0.19.1