update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.79
+      value: 0.85
 ---
 
 <!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6637
-- Accuracy: 0.79
+- Loss: 0.7011
+- Accuracy: 0.85
 
 ## Model description
 
@@ -59,22 +59,32 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9842        | 1.0   | 113  | 1.8107          | 0.53     |
-| 1.3426        | 2.0   | 226  | 1.2064          | 0.7      |
-| 1.0421        | 3.0   | 339  | 1.0109          | 0.71     |
-| 0.871         | 4.0   | 452  | 0.8944          | 0.72     |
-| 0.6817        | 5.0   | 565  | 0.7643          | 0.77     |
-| 0.4104        | 6.0   | 678  | 0.7248          | 0.79     |
-| 0.4996        | 7.0   | 791  | 0.6640          | 0.79     |
-| 0.2037        | 8.0   | 904  | 0.6693          | 0.78     |
-| 0.3115        | 9.0   | 1017 | 0.6709          | 0.78     |
-| 0.1829        | 10.0  | 1130 | 0.6637          | 0.79     |
+| 2.1633        | 1.0   | 113  | 2.0443          | 0.48     |
+| 1.5137        | 2.0   | 226  | 1.4296          | 0.63     |
+| 1.2242        | 3.0   | 339  | 1.0546          | 0.72     |
+| 0.9275        | 4.0   | 452  | 0.9730          | 0.73     |
+| 0.6252        | 5.0   | 565  | 0.6862          | 0.84     |
+| 0.403         | 6.0   | 678  | 0.5890          | 0.8      |
+| 0.5256        | 7.0   | 791  | 0.5414          | 0.84     |
+| 0.124         | 8.0   | 904  | 0.5469          | 0.81     |
+| 0.1207        | 9.0   | 1017 | 0.5683          | 0.82     |
+| 0.0434        | 10.0  | 1130 | 0.6445          | 0.83     |
+| 0.0107        | 11.0  | 1243 | 0.7085          | 0.83     |
+| 0.134         | 12.0  | 1356 | 0.6363          | 0.85     |
+| 0.0056        | 13.0  | 1469 | 0.6332          | 0.85     |
+| 0.0045        | 14.0  | 1582 | 0.6881          | 0.85     |
+| 0.004         | 15.0  | 1695 | 0.6204          | 0.86     |
+| 0.0033        | 16.0  | 1808 | 0.7015          | 0.84     |
+| 0.046         | 17.0  | 1921 | 0.6880          | 0.85     |
+| 0.0028        | 18.0  | 2034 | 0.6841          | 0.84     |
+| 0.0027        | 19.0  | 2147 | 0.6894          | 0.85     |
+| 0.0028        | 20.0  | 2260 | 0.7011          | 0.85     |
 
 
 ### Framework versions