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: 0.7031
-- Accuracy: 0.82
+- Loss: 0.5358
+- Accuracy: 0.88
 
 ## Model description
 
@@ -38,39 +38,29 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 0.0001
 - 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: 20
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.2612        | 1.0   | 57   | 2.2511          | 0.26     |
-| 2.1275        | 2.0   | 114  | 2.0384          | 0.36     |
-| 1.8071        | 3.0   | 171  | 1.7399          | 0.52     |
-| 1.6381        | 4.0   | 228  | 1.5693          | 0.61     |
-| 1.4188        | 5.0   | 285  | 1.3573          | 0.61     |
-| 1.2974        | 6.0   | 342  | 1.2103          | 0.72     |
-| 1.2146        | 7.0   | 399  | 1.1800          | 0.69     |
-| 1.0725        | 8.0   | 456  | 1.0126          | 0.77     |
-| 1.0492        | 9.0   | 513  | 0.9821          | 0.74     |
-| 1.0529        | 10.0  | 570  | 0.9347          | 0.77     |
-| 0.895         | 11.0  | 627  | 0.8520          | 0.79     |
-| 0.7692        | 12.0  | 684  | 0.8451          | 0.8      |
-| 0.6566        | 13.0  | 741  | 0.7763          | 0.82     |
-| 0.5885        | 14.0  | 798  | 0.7852          | 0.8      |
-| 0.619         | 15.0  | 855  | 0.7443          | 0.8      |
-| 0.5572        | 16.0  | 912  | 0.7444          | 0.79     |
-| 0.6493        | 17.0  | 969  | 0.7024          | 0.83     |
-| 0.5499        | 18.0  | 1026 | 0.7137          | 0.81     |
-| 0.5923        | 19.0  | 1083 | 0.7059          | 0.81     |
-| 0.5556        | 20.0  | 1140 | 0.7031          | 0.82     |
+| 1.8758        | 1.0   | 57   | 1.7723          | 0.51     |
+| 1.2291        | 2.0   | 114  | 1.1713          | 0.69     |
+| 0.8029        | 3.0   | 171  | 0.8953          | 0.75     |
+| 0.7314        | 4.0   | 228  | 0.8242          | 0.73     |
+| 0.3424        | 5.0   | 285  | 0.6117          | 0.82     |
+| 0.229         | 6.0   | 342  | 0.5272          | 0.82     |
+| 0.1571        | 7.0   | 399  | 0.5470          | 0.87     |
+| 0.0777        | 8.0   | 456  | 0.5393          | 0.88     |
+| 0.0539        | 9.0   | 513  | 0.5087          | 0.88     |
+| 0.0688        | 10.0  | 570  | 0.5358          | 0.88     |
 
 
 ### Framework versions