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convnext-tiny-224-finetuned-eurosat-albumentations

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paom commited on May 30, 2023

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update model card README.md

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@@ -29,7 +29,7 @@ should probably proofread and complete it, then remove this comment. -->
 # convnext-tiny-224-finetuned-eurosat-albumentations
-This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.6948
 - Accuracy: 0.0
@@ -60,15 +60,32 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
 | No log        | 1.0   | 1    | 0.6948          | 0.0      |
-| No log        | 2.0   | 2    | 0.3507          | 0.0      |
-| No log        | 3.0   | 3    | 0.2292          | 0.0      |
 ### Framework versions

 # convnext-tiny-224-finetuned-eurosat-albumentations
+This model is a fine-tuned version of [paom/convnext-tiny-224-finetuned-eurosat-albumentations](https://huggingface.co/paom/convnext-tiny-224-finetuned-eurosat-albumentations) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.6948
 - Accuracy: 0.0
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
 | No log        | 1.0   | 1    | 0.6948          | 0.0      |
+| No log        | 2.0   | 2    | 0.5057          | 0.0      |
+| No log        | 3.0   | 3    | 0.2286          | 0.0      |
+| No log        | 4.0   | 4    | 0.0823          | 0.0      |
+| No log        | 5.0   | 5    | 0.0320          | 0.0      |
+| No log        | 6.0   | 6    | 0.0489          | 0.0      |
+| No log        | 7.0   | 7    | 0.0881          | 0.0      |
+| No log        | 8.0   | 8    | 0.1134          | 0.0      |
+| No log        | 9.0   | 9    | 0.1179          | 0.0      |
+| 0.0638        | 10.0  | 10   | 0.1054          | 0.0      |
+| 0.0638        | 11.0  | 11   | 0.0826          | 0.0      |
+| 0.0638        | 12.0  | 12   | 0.0587          | 0.0      |
+| 0.0638        | 13.0  | 13   | 0.0386          | 0.0      |
+| 0.0638        | 14.0  | 14   | 0.0241          | 0.0      |
+| 0.0638        | 15.0  | 15   | 0.0158          | 0.0      |
+| 0.0638        | 16.0  | 16   | 0.0115          | 0.0      |
+| 0.0638        | 17.0  | 17   | 0.0096          | 0.0      |
+| 0.0638        | 18.0  | 18   | 0.0087          | 0.0      |
+| 0.0638        | 19.0  | 19   | 0.0084          | 0.0      |
+| 0.0048        | 20.0  | 20   | 0.0083          | 0.0      |
 ### Framework versions