luciagil
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Human-action-swin

Image Classification

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luciagil commited on Apr 6, 2024

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README.md +15 -6
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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7221
-- Accuracy: 0.7738
 ## Model description
@@ -46,15 +46,24 @@ 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.4273        | 0.99  | 78   | 1.0470          | 0.6710   |
-| 1.0813        | 1.99  | 157  | 0.7848          | 0.7512   |
-| 0.9644        | 2.97  | 234  | 0.7221          | 0.7738   |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.5231
+- Accuracy: 0.8377
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 12
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8248        | 0.99  | 78   | 0.7299          | 0.7667   |
+| 0.806         | 1.99  | 157  | 0.6541          | 0.7944   |
+| 0.8544        | 3.0   | 236  | 0.6443          | 0.7996   |
+| 0.8503        | 4.0   | 315  | 0.5965          | 0.8179   |
+| 0.7538        | 4.99  | 393  | 0.5674          | 0.8282   |
+| 0.6921        | 5.99  | 472  | 0.5941          | 0.8175   |
+| 0.7214        | 7.0   | 551  | 0.5721          | 0.8246   |
+| 0.6402        | 8.0   | 630  | 0.5433          | 0.8361   |
+| 0.5899        | 8.99  | 708  | 0.5323          | 0.8425   |
+| 0.6688        | 9.99  | 787  | 0.5213          | 0.8409   |
+| 0.5948        | 11.0  | 866  | 0.5244          | 0.8385   |
+| 0.5818        | 11.89 | 936  | 0.5231          | 0.8377   |
 ### Framework versions

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