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JaydenJH
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swinv2-tiny-patch4-window8-256-finetuned-eurosat

Image Classification
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swinv2
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5112
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- - Accuracy: 0.7969
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  ## Model description
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@@ -46,17 +46,32 @@ 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: 5
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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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- | 0.6594 | 0.9955 | 167 | 0.6860 | 0.7426 |
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- | 0.5427 | 1.9970 | 335 | 0.5231 | 0.7836 |
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- | 0.523 | 2.9985 | 503 | 0.5246 | 0.7912 |
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- | 0.4991 | 4.0 | 671 | 0.5136 | 0.7950 |
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- | 0.4512 | 4.9776 | 835 | 0.5112 | 0.7969 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6760
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+ - Accuracy: 0.8170
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  ## Model description
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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: 20
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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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+ | 0.2519 | 0.9955 | 167 | 0.7302 | 0.8017 |
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+ | 0.2407 | 1.9970 | 335 | 0.7095 | 0.7836 |
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+ | 0.3423 | 2.9985 | 503 | 0.7016 | 0.7884 |
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+ | 0.4687 | 4.0 | 671 | 0.6480 | 0.7969 |
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+ | 0.4789 | 4.9955 | 838 | 0.5132 | 0.8160 |
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+ | 0.4417 | 5.9970 | 1006 | 0.5321 | 0.8065 |
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+ | 0.435 | 6.9985 | 1174 | 0.5770 | 0.8093 |
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+ | 0.4106 | 8.0 | 1342 | 0.5650 | 0.8189 |
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+ | 0.4216 | 8.9955 | 1509 | 0.5535 | 0.8132 |
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+ | 0.3786 | 9.9970 | 1677 | 0.5745 | 0.8179 |
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+ | 0.3536 | 10.9985 | 1845 | 0.6322 | 0.8046 |
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+ | 0.4842 | 12.0 | 2013 | 0.7200 | 0.8103 |
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+ | 0.3095 | 12.9955 | 2180 | 0.6996 | 0.8112 |
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+ | 0.2603 | 13.9970 | 2348 | 0.7004 | 0.8065 |
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+ | 0.2838 | 14.9985 | 2516 | 0.6331 | 0.8227 |
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+ | 0.3449 | 16.0 | 2684 | 0.6788 | 0.8122 |
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+ | 0.253 | 16.9955 | 2851 | 0.6940 | 0.8103 |
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+ | 0.2647 | 17.9970 | 3019 | 0.6770 | 0.8132 |
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+ | 0.2991 | 18.9985 | 3187 | 0.6647 | 0.8189 |
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+ | 0.26 | 19.9106 | 3340 | 0.6760 | 0.8170 |
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  ### Framework versions
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