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10-convnextv2-nano-22k-384-finetuned-spiderTraining20-500

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zkdeng commited on Sep 13

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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2969
-- Accuracy: 0.9099
-- Precision: 0.9049
-- Recall: 0.9057
-- F1: 0.9048
 ## Model description
@@ -61,14 +61,14 @@ The following hyperparameters were used during training:
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
 | 1.7156        | 1.0   | 80   | 1.4314          | 0.6316   | 0.6182    | 0.6246 | 0.6155 |
 | 0.7565        | 2.0   | 160  | 0.6340          | 0.8168   | 0.8213    | 0.8074 | 0.8095 |
-| 0.5802        | 3.0   | 240  | 0.4633          | 0.8589   | 0.8566    | 0.8545 | 0.8539 |
-| 0.4765        | 4.0   | 320  | 0.4006          | 0.8759   | 0.8746    | 0.8709 | 0.8708 |
-| 0.3644        | 5.0   | 400  | 0.3530          | 0.9019   | 0.8995    | 0.8984 | 0.8979 |
-| 0.3622        | 6.0   | 480  | 0.3326          | 0.9049   | 0.9019    | 0.9020 | 0.9013 |
-| 0.3232        | 7.0   | 560  | 0.3180          | 0.8939   | 0.8910    | 0.8889 | 0.8892 |
-| 0.2968        | 8.0   | 640  | 0.3018          | 0.9089   | 0.9050    | 0.9039 | 0.9039 |
-| 0.285         | 9.0   | 720  | 0.3097          | 0.9029   | 0.8979    | 0.8991 | 0.8974 |
-| 0.2889        | 10.0  | 800  | 0.2969          | 0.9099   | 0.9049    | 0.9057 | 0.9048 |
 ### Framework versions

 This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2966
+- Accuracy: 0.9109
+- Precision: 0.9058
+- Recall: 0.9065
+- F1: 0.9057
 ## Model description
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
 | 1.7156        | 1.0   | 80   | 1.4314          | 0.6316   | 0.6182    | 0.6246 | 0.6155 |
 | 0.7565        | 2.0   | 160  | 0.6340          | 0.8168   | 0.8213    | 0.8074 | 0.8095 |
+| 0.5802        | 3.0   | 240  | 0.4632          | 0.8589   | 0.8566    | 0.8545 | 0.8539 |
+| 0.4767        | 4.0   | 320  | 0.4006          | 0.8759   | 0.8748    | 0.8710 | 0.8708 |
+| 0.3648        | 5.0   | 400  | 0.3529          | 0.8999   | 0.8976    | 0.8965 | 0.8960 |
+| 0.3623        | 6.0   | 480  | 0.3326          | 0.9059   | 0.9030    | 0.9031 | 0.9024 |
+| 0.3238        | 7.0   | 560  | 0.3178          | 0.8939   | 0.8910    | 0.8889 | 0.8892 |
+| 0.2975        | 8.0   | 640  | 0.3016          | 0.9079   | 0.9037    | 0.9029 | 0.9028 |
+| 0.2852        | 9.0   | 720  | 0.3090          | 0.9029   | 0.8979    | 0.8991 | 0.8974 |
+| 0.2893        | 10.0  | 800  | 0.2966          | 0.9109   | 0.9058    | 0.9065 | 0.9057 |
 ### Framework versions