update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.85
+      value: 0.87
 ---
 
 <!-- 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: 0.6034
-- Accuracy: 0.85
+- Loss: 0.6210
+- Accuracy: 0.87
 
 ## Model description
 
@@ -59,22 +59,27 @@ 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: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0064        | 1.0   | 113  | 1.8202          | 0.41     |
-| 1.302         | 2.0   | 226  | 1.1734          | 0.73     |
-| 1.0377        | 3.0   | 339  | 0.9812          | 0.71     |
-| 0.8217        | 4.0   | 452  | 0.8479          | 0.74     |
-| 0.5438        | 5.0   | 565  | 0.6818          | 0.82     |
-| 0.3907        | 6.0   | 678  | 0.6460          | 0.82     |
-| 0.4398        | 7.0   | 791  | 0.5976          | 0.86     |
-| 0.1695        | 8.0   | 904  | 0.5846          | 0.85     |
-| 0.2673        | 9.0   | 1017 | 0.6181          | 0.84     |
-| 0.1348        | 10.0  | 1130 | 0.6034          | 0.85     |
+| 2.1281        | 1.0   | 113  | 1.9810          | 0.46     |
+| 1.4934        | 2.0   | 226  | 1.3605          | 0.62     |
+| 1.1668        | 3.0   | 339  | 0.9967          | 0.75     |
+| 0.9904        | 4.0   | 452  | 0.8179          | 0.74     |
+| 0.7369        | 5.0   | 565  | 0.6686          | 0.84     |
+| 0.5161        | 6.0   | 678  | 0.6022          | 0.8      |
+| 0.5269        | 7.0   | 791  | 0.5942          | 0.85     |
+| 0.2076        | 8.0   | 904  | 0.5678          | 0.86     |
+| 0.3907        | 9.0   | 1017 | 0.5466          | 0.85     |
+| 0.2112        | 10.0  | 1130 | 0.5610          | 0.86     |
+| 0.0678        | 11.0  | 1243 | 0.5933          | 0.87     |
+| 0.063         | 12.0  | 1356 | 0.6582          | 0.81     |
+| 0.0342        | 13.0  | 1469 | 0.6052          | 0.88     |
+| 0.0209        | 14.0  | 1582 | 0.6139          | 0.88     |
+| 0.021         | 15.0  | 1695 | 0.6210          | 0.87     |
 
 
 ### Framework versions