jeemsterri
/

fish_classification

Image Classification

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Jeems commited on Mar 20

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88b5320

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1 Parent(s): 13f4a45

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README.md +12 -12

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@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9984615384615385
     - name: F1
       type: f1
-      value: 0.9985045948203843
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1970
-- Accuracy: 0.9985
-- F1: 0.9985
 ## Model description
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 1.0209        | 1.0   | 71   | 0.7163          | 0.9969   | 0.9970 |
-| 0.4711        | 2.0   | 142  | 0.3916          | 0.9985   | 0.9985 |
-| 0.2876        | 3.0   | 213  | 0.2855          | 0.9985   | 0.9985 |
-| 0.2222        | 4.0   | 284  | 0.2376          | 0.9985   | 0.9985 |
-| 0.1915        | 5.0   | 355  | 0.2120          | 0.9985   | 0.9985 |
-| 0.1754        | 6.0   | 426  | 0.1990          | 0.9985   | 0.9985 |
-| 0.1682        | 7.0   | 497  | 0.1970          | 0.9985   | 0.9985 |
 ### Framework versions

     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.9969230769230769
     - name: F1
       type: f1
+      value: 0.9970182569296375
 ---
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2213
+- Accuracy: 0.9969
+- F1: 0.9970
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.5189        | 1.0   | 71   | 1.0828          | 0.9969   | 0.9970 |
+| 0.7083        | 2.0   | 142  | 0.5398          | 0.9954   | 0.9955 |
+| 0.3727        | 3.0   | 213  | 0.3473          | 0.9954   | 0.9955 |
+| 0.2624        | 4.0   | 284  | 0.2734          | 0.9985   | 0.9985 |
+| 0.2184        | 5.0   | 355  | 0.2401          | 0.9985   | 0.9985 |
+| 0.1972        | 6.0   | 426  | 0.2238          | 0.9985   | 0.9985 |
+| 0.1879        | 7.0   | 497  | 0.2213          | 0.9969   | 0.9970 |
 ### Framework versions