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swin-tiny-patch4-window7-224-finetuned-eurosat

Image Classification
Transformers
PyTorch
swin
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +15 -15
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@@ -4,7 +4,7 @@ base_model: microsoft/swin-tiny-patch4-window7-224
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  tags:
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  - generated_from_trainer
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  datasets:
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- - imagefolder
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  metrics:
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  - accuracy
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  model-index:
@@ -14,15 +14,15 @@ 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: 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: 0.9803703703703703
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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
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # swin-tiny-patch4-window7-224-finetuned-eurosat
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- This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0592
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- - Accuracy: 0.9804
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  ## Model description
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@@ -67,14 +67,14 @@ 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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- | 0.2484 | 1.0 | 190 | 0.1036 | 0.9685 |
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- | 0.219 | 2.0 | 380 | 0.0825 | 0.9730 |
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- | 0.121 | 3.0 | 570 | 0.0592 | 0.9804 |
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  ### Framework versions
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- - Transformers 4.33.2
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- - Pytorch 2.0.1+cu117
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- - Datasets 2.14.5
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  - Tokenizers 0.13.3
 
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  tags:
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  - generated_from_trainer
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  datasets:
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+ - cifar10
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  metrics:
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  - accuracy
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  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: cifar10
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+ type: cifar10
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+ config: plain_text
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  split: train
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+ args: plain_text
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.973
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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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  # swin-tiny-patch4-window7-224-finetuned-eurosat
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+ This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the cifar10 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0799
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+ - Accuracy: 0.973
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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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+ | 0.5238 | 1.0 | 351 | 0.1417 | 0.9512 |
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+ | 0.3708 | 2.0 | 703 | 0.0975 | 0.9688 |
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+ | 0.3201 | 2.99 | 1053 | 0.0799 | 0.973 |
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  ### Framework versions
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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  - Tokenizers 0.13.3