update model card README.md

README.md

@@ -18,8 +18,8 @@ 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: 0.6231
-- Accuracy: 0.83
+- Loss: 1.0379
+- Accuracy: 0.81
 
 ## Model description
 
@@ -45,22 +45,32 @@ 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 |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7262        | 1.0   | 113  | 1.8018          | 0.41     |
-| 1.1879        | 2.0   | 226  | 1.2414          | 0.64     |
-| 1.0662        | 3.0   | 339  | 0.9183          | 0.76     |
-| 0.6538        | 4.0   | 452  | 0.6994          | 0.83     |
-| 0.4435        | 5.0   | 565  | 0.6452          | 0.82     |
-| 0.2902        | 6.0   | 678  | 0.5580          | 0.85     |
-| 0.1912        | 7.0   | 791  | 0.6249          | 0.82     |
-| 0.2514        | 8.0   | 904  | 0.6166          | 0.83     |
-| 0.1347        | 9.0   | 1017 | 0.6010          | 0.84     |
-| 0.2313        | 10.0  | 1130 | 0.6231          | 0.83     |
+| 2.0307        | 1.0   | 113  | 2.0561          | 0.41     |
+| 1.4208        | 2.0   | 226  | 1.4850          | 0.63     |
+| 1.1959        | 3.0   | 339  | 1.0617          | 0.66     |
+| 0.6929        | 4.0   | 452  | 0.8228          | 0.74     |
+| 0.5104        | 5.0   | 565  | 0.6969          | 0.77     |
+| 0.4735        | 6.0   | 678  | 0.7412          | 0.79     |
+| 0.2185        | 7.0   | 791  | 0.6586          | 0.76     |
+| 0.3087        | 8.0   | 904  | 0.8234          | 0.78     |
+| 0.1066        | 9.0   | 1017 | 0.8210          | 0.8      |
+| 0.0841        | 10.0  | 1130 | 1.0040          | 0.8      |
+| 0.0387        | 11.0  | 1243 | 0.9195          | 0.81     |
+| 0.0091        | 12.0  | 1356 | 0.9208          | 0.82     |
+| 0.006         | 13.0  | 1469 | 0.9190          | 0.81     |
+| 0.0051        | 14.0  | 1582 | 0.9796          | 0.8      |
+| 0.0038        | 15.0  | 1695 | 0.9823          | 0.8      |
+| 0.0035        | 16.0  | 1808 | 1.0252          | 0.8      |
+| 0.0032        | 17.0  | 1921 | 1.0172          | 0.8      |
+| 0.0032        | 18.0  | 2034 | 1.0433          | 0.81     |
+| 0.0029        | 19.0  | 2147 | 1.0577          | 0.81     |
+| 0.0029        | 20.0  | 2260 | 1.0379          | 0.81     |
 
 
 ### Framework versions