update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.81
+      value: 0.83
 ---
 
 <!-- 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: 0.9143
-- Accuracy: 0.81
+- Loss: 0.8934
+- Accuracy: 0.83
 
 ## 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.8743        | 1.0   | 113  | 1.5757          | 0.54     |
-| 1.064         | 2.0   | 226  | 1.0082          | 0.62     |
-| 0.8998        | 3.0   | 339  | 0.9248          | 0.72     |
-| 0.7369        | 4.0   | 452  | 0.9222          | 0.71     |
-| 0.4974        | 5.0   | 565  | 0.7056          | 0.77     |
-| 0.2791        | 6.0   | 678  | 0.9696          | 0.78     |
-| 0.1814        | 7.0   | 791  | 0.8932          | 0.8      |
-| 0.0229        | 8.0   | 904  | 0.8166          | 0.82     |
-| 0.0193        | 9.0   | 1017 | 0.8444          | 0.81     |
-| 0.0435        | 10.0  | 1130 | 0.9143          | 0.81     |
+| 1.9361        | 1.0   | 113  | 1.7009          | 0.47     |
+| 1.2014        | 2.0   | 226  | 1.0356          | 0.68     |
+| 0.943         | 3.0   | 339  | 0.8529          | 0.76     |
+| 0.6362        | 4.0   | 452  | 0.9040          | 0.72     |
+| 0.4754        | 5.0   | 565  | 0.7102          | 0.79     |
+| 0.4526        | 6.0   | 678  | 0.6811          | 0.8      |
+| 0.2139        | 7.0   | 791  | 0.7872          | 0.83     |
+| 0.0133        | 8.0   | 904  | 0.8736          | 0.83     |
+| 0.0089        | 9.0   | 1017 | 0.8696          | 0.82     |
+| 0.0639        | 10.0  | 1130 | 0.9064          | 0.85     |
+| 0.0026        | 11.0  | 1243 | 0.9165          | 0.82     |
+| 0.1601        | 12.0  | 1356 | 0.8257          | 0.86     |
+| 0.0017        | 13.0  | 1469 | 0.8388          | 0.85     |
+| 0.0018        | 14.0  | 1582 | 0.8639          | 0.84     |
+| 0.0017        | 15.0  | 1695 | 0.8934          | 0.83     |
 
 
 ### Framework versions