update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.84
+      value: 0.85
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ 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: 0.6273
-- Accuracy: 0.84
+- Loss: 0.5990
+- Accuracy: 0.85
 
 ## Model description
 
@@ -51,34 +51,39 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 4e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 15
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.253         | 1.0   | 57   | 2.2124          | 0.43     |
-| 1.8499        | 2.0   | 114  | 1.7776          | 0.56     |
-| 1.4569        | 3.0   | 171  | 1.4535          | 0.69     |
-| 1.3715        | 4.0   | 228  | 1.2296          | 0.74     |
-| 1.097         | 5.0   | 285  | 1.0841          | 0.73     |
-| 0.9876        | 6.0   | 342  | 0.9591          | 0.76     |
-| 0.8501        | 7.0   | 399  | 0.8912          | 0.75     |
-| 0.8233        | 8.0   | 456  | 0.8314          | 0.75     |
-| 0.7055        | 9.0   | 513  | 0.7713          | 0.77     |
-| 0.5709        | 10.0  | 570  | 0.7053          | 0.81     |
-| 0.4924        | 11.0  | 627  | 0.7325          | 0.79     |
-| 0.4679        | 12.0  | 684  | 0.6562          | 0.8      |
-| 0.496         | 13.0  | 741  | 0.6376          | 0.85     |
-| 0.3827        | 14.0  | 798  | 0.6331          | 0.84     |
-| 0.4118        | 15.0  | 855  | 0.6273          | 0.84     |
+| 2.2435        | 1.0   | 57   | 2.2120          | 0.4      |
+| 1.7899        | 2.0   | 114  | 1.7033          | 0.51     |
+| 1.3321        | 3.0   | 171  | 1.3450          | 0.66     |
+| 1.2031        | 4.0   | 228  | 1.1139          | 0.68     |
+| 0.9076        | 5.0   | 285  | 0.9759          | 0.72     |
+| 0.8037        | 6.0   | 342  | 0.8595          | 0.7      |
+| 0.6698        | 7.0   | 399  | 0.7222          | 0.78     |
+| 0.5379        | 8.0   | 456  | 0.6924          | 0.81     |
+| 0.4473        | 9.0   | 513  | 0.6366          | 0.82     |
+| 0.2804        | 10.0  | 570  | 0.5824          | 0.83     |
+| 0.251         | 11.0  | 627  | 0.6684          | 0.8      |
+| 0.1587        | 12.0  | 684  | 0.5439          | 0.85     |
+| 0.161         | 13.0  | 741  | 0.5983          | 0.84     |
+| 0.0886        | 14.0  | 798  | 0.6164          | 0.83     |
+| 0.0726        | 15.0  | 855  | 0.5598          | 0.85     |
+| 0.1023        | 16.0  | 912  | 0.5753          | 0.85     |
+| 0.0608        | 17.0  | 969  | 0.5933          | 0.85     |
+| 0.04          | 18.0  | 1026 | 0.5728          | 0.84     |
+| 0.0381        | 19.0  | 1083 | 0.5907          | 0.85     |
+| 0.0387        | 20.0  | 1140 | 0.5990          | 0.85     |
 
 
 ### Framework versions