fydhfzh
/

hubert-classifier

@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.4231
-- Accuracy: 0.0993
-- Precision: 0.0191
-- Recall: 0.0993
-- F1: 0.0296
-- Binary: 0.3603
 ## Model description
@@ -59,17 +59,17 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
-| No log        | 0.86  | 50   | 4.4031          | 0.0218   | 0.0042    | 0.0218 | 0.0061 | 0.1886 |
-| No log        | 1.72  | 100  | 4.1752          | 0.0363   | 0.0204    | 0.0363 | 0.0100 | 0.3102 |
-| No log        | 2.59  | 150  | 3.9334          | 0.0363   | 0.0159    | 0.0363 | 0.0125 | 0.3102 |
-| No log        | 3.45  | 200  | 3.7751          | 0.0557   | 0.0270    | 0.0557 | 0.0268 | 0.3266 |
-| No log        | 4.31  | 250  | 3.6877          | 0.0775   | 0.0241    | 0.0775 | 0.0314 | 0.3383 |
-| No log        | 5.17  | 300  | 3.5839          | 0.0920   | 0.0220    | 0.0920 | 0.0329 | 0.3550 |
-| No log        | 6.03  | 350  | 3.5119          | 0.0920   | 0.0219    | 0.0920 | 0.0327 | 0.3586 |
-| No log        | 6.9   | 400  | 3.4851          | 0.0872   | 0.0274    | 0.0872 | 0.0283 | 0.3508 |
-| No log        | 7.76  | 450  | 3.4593          | 0.0920   | 0.0221    | 0.0920 | 0.0312 | 0.3552 |
-| 3.8751        | 8.62  | 500  | 3.4240          | 0.1017   | 0.0223    | 0.1017 | 0.0328 | 0.3610 |
-| 3.8751        | 9.48  | 550  | 3.4231          | 0.0993   | 0.0191    | 0.0993 | 0.0296 | 0.3603 |
 ### Framework versions

 This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 3.2561
+- Accuracy: 0.2155
+- Precision: 0.1870
+- Recall: 0.2155
+- F1: 0.1453
+- Binary: 0.4380
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| No log        | 0.86  | 50   | 4.2865          | 0.0291   | 0.0034    | 0.0291 | 0.0043 | 0.2661 |
+| No log        | 1.72  | 100  | 4.0141          | 0.0460   | 0.0306    | 0.0460 | 0.0187 | 0.3199 |
+| No log        | 2.59  | 150  | 3.8172          | 0.0630   | 0.0204    | 0.0630 | 0.0214 | 0.3378 |
+| No log        | 3.45  | 200  | 3.7045          | 0.0896   | 0.0534    | 0.0896 | 0.0533 | 0.3431 |
+| No log        | 4.31  | 250  | 3.5695          | 0.1308   | 0.0844    | 0.1308 | 0.0796 | 0.3785 |
+| No log        | 5.17  | 300  | 3.4883          | 0.1622   | 0.1140    | 0.1622 | 0.1002 | 0.3954 |
+| No log        | 6.03  | 350  | 3.4447          | 0.1622   | 0.1145    | 0.1622 | 0.1005 | 0.3925 |
+| No log        | 6.9   | 400  | 3.3482          | 0.1671   | 0.0972    | 0.1671 | 0.1026 | 0.4077 |
+| No log        | 7.76  | 450  | 3.3042          | 0.1961   | 0.1424    | 0.1961 | 0.1295 | 0.4228 |
+| 3.7796        | 8.62  | 500  | 3.2724          | 0.2131   | 0.1898    | 0.2131 | 0.1472 | 0.4370 |
+| 3.7796        | 9.48  | 550  | 3.2561          | 0.2155   | 0.1870    | 0.2155 | 0.1453 | 0.4380 |
 ### Framework versions

runs/Jun17_20-21-51_LAPTOP-1GID9RGH/events.out.tfevents.1718630512.LAPTOP-1GID9RGH.14224.0 CHANGED Viewed

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