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dinov2-small-imagenet1k-1-layer-finetuned-noh

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hoanbklucky commited on 2 days ago

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README.md +12 -12
model.safetensors +1 -1

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@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/dinov2-small-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-small-imagenet1k-1-layer) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3058
-- Accuracy: 0.8982
 ## Model description
@@ -53,16 +53,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.5315        | 1.0    | 23   | 1.2674          | 0.2479   |
-| 0.4629        | 2.0    | 46   | 0.5134          | 0.7882   |
-| 0.4368        | 3.0    | 69   | 0.3058          | 0.8982   |
-| 0.4123        | 4.0    | 92   | 0.4148          | 0.8046   |
-| 0.3301        | 5.0    | 115  | 0.3520          | 0.8736   |
-| 0.2907        | 6.0    | 138  | 0.4415          | 0.8440   |
-| 0.2809        | 7.0    | 161  | 0.5786          | 0.7521   |
-| 0.2243        | 8.0    | 184  | 0.4724          | 0.8752   |
-| 0.1968        | 9.0    | 207  | 0.5452          | 0.8703   |
-| 0.1601        | 9.5778 | 220  | 0.5386          | 0.8440   |
 ### Framework versions

 This model is a fine-tuned version of [facebook/dinov2-small-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-small-imagenet1k-1-layer) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.3969
+- Accuracy: 0.8489
 ## Model description
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.6331        | 1.0    | 23   | 0.5416          | 0.7652   |
+| 0.4913        | 2.0    | 46   | 0.3755          | 0.9080   |
+| 0.4642        | 3.0    | 69   | 0.7141          | 0.6141   |
+| 0.4451        | 4.0    | 92   | 0.4348          | 0.8046   |
+| 0.4095        | 5.0    | 115  | 0.5060          | 0.8030   |
+| 0.3399        | 6.0    | 138  | 0.5464          | 0.7373   |
+| 0.3304        | 7.0    | 161  | 0.3274          | 0.8883   |
+| 0.3539        | 8.0    | 184  | 0.3893          | 0.8604   |
+| 0.2849        | 9.0    | 207  | 0.3758          | 0.8637   |
+| 0.2605        | 9.5778 | 220  | 0.3969          | 0.8489   |
 ### Framework versions

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