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pk3388
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vit-msn-small-finetuned-eurosat

Image Classification
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Safetensors
vit_msn
Generated from Trainer
Eval Results
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  1. README.md +11 -8
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +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: 0.5684210526315789
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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 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3137
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- - Accuracy: 0.5684
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  ## Model description
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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: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -61,15 +61,18 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 3
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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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- | 2.2554 | 0.9362 | 11 | 1.8217 | 0.4053 |
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- | 1.6448 | 1.9574 | 23 | 1.4679 | 0.4895 |
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- | 1.3339 | 2.8085 | 33 | 1.3137 | 0.5684 |
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8
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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/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6649
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+ - Accuracy: 0.8
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 6
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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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+ | 1.115 | 0.9362 | 11 | 1.0397 | 0.6526 |
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+ | 0.8536 | 1.9574 | 23 | 0.7698 | 0.7579 |
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+ | 0.5677 | 2.9787 | 35 | 0.7200 | 0.7895 |
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+ | 0.419 | 4.0 | 47 | 0.7286 | 0.7842 |
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+ | 0.3365 | 4.9362 | 58 | 0.6607 | 0.8105 |
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+ | 0.2317 | 5.6170 | 66 | 0.6649 | 0.8 |
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  ### Framework versions
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