embunna
/

resnet-18

Image Classification

Generated from Trainer

Inference Endpoints

Model card Files Files and versions Metrics Training metrics Community

embunna commited on Jun 6

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e410039

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README.md +8 -8
model.safetensors +1 -1

README.md CHANGED Viewed

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.3958333333333333
 ---
 <!-- 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. -->
 This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2853997620560357538714861174784.0000
-- Accuracy: 0.3958
 ## Model description
@@ -65,11 +65,11 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss                        | Epoch  | Step | Validation Loss                      | Accuracy |
-|:------------------------------------:|:------:|:----:|:------------------------------------:|:--------:|
-| No log                               | 0.8889 | 6    | 2853997620560357538714861174784.0000 | 0.3958   |
-| 3195940475249625978836740997120.0000 | 1.9259 | 13   | 2853997620560357538714861174784.0000 | 0.3958   |
-| 3195940475249625978836740997120.0000 | 2.6667 | 18   | 2853997620560357538714861174784.0000 | 0.3958   |
 ### Framework versions

     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.2857142857142857
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
+- Loss: 11425938732811038938338101821440.0000
+- Accuracy: 0.2857
 ## Model description
 ### Training results
+| Training Loss                         | Epoch  | Step | Validation Loss                       | Accuracy |
+|:-------------------------------------:|:------:|:----:|:-------------------------------------:|:--------:|
+| No log                                | 0.9091 | 5    | 11425938732811038938338101821440.0000 | 0.2857   |
+| 10876880651531499783855888400384.0000 | 2.0    | 11   | 11425938732811038938338101821440.0000 | 0.2857   |
+| 10876880651531499783855888400384.0000 | 2.7273 | 15   | 11425938732811038938338101821440.0000 | 0.2857   |
 ### Framework versions

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