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: 0.7824
-- Accuracy: 0.8
+- Loss: 0.6711
+- Accuracy: 0.82
 
 ## Model description
 
@@ -38,7 +38,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 2e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -46,18 +46,33 @@ 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: 5
+- num_epochs: 20
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.6129        | 1.0   | 113  | 1.7019          | 0.52     |
-| 1.1591        | 2.0   | 226  | 1.1881          | 0.73     |
-| 1.0244        | 3.0   | 339  | 0.9023          | 0.8      |
-| 0.7501        | 4.0   | 452  | 0.8744          | 0.72     |
-| 0.6153        | 5.0   | 565  | 0.7824          | 0.8      |
+| 2.1962        | 1.0   | 113  | 2.2220          | 0.29     |
+| 1.9431        | 2.0   | 226  | 1.8877          | 0.5      |
+| 1.634         | 3.0   | 339  | 1.5106          | 0.63     |
+| 1.3403        | 4.0   | 452  | 1.3191          | 0.66     |
+| 1.1067        | 5.0   | 565  | 1.1082          | 0.68     |
+| 1.0416        | 6.0   | 678  | 1.0664          | 0.72     |
+| 0.7723        | 7.0   | 791  | 0.9729          | 0.77     |
+| 0.8281        | 8.0   | 904  | 0.8799          | 0.78     |
+| 0.6344        | 9.0   | 1017 | 0.8142          | 0.77     |
+| 0.8819        | 10.0  | 1130 | 0.8719          | 0.73     |
+| 0.4279        | 11.0  | 1243 | 0.8150          | 0.78     |
+| 0.425         | 12.0  | 1356 | 0.7137          | 0.81     |
+| 0.2749        | 13.0  | 1469 | 0.6987          | 0.8      |
+| 0.2182        | 14.0  | 1582 | 0.6849          | 0.82     |
+| 0.2128        | 15.0  | 1695 | 0.6918          | 0.82     |
+| 0.1831        | 16.0  | 1808 | 0.6600          | 0.81     |
+| 0.1517        | 17.0  | 1921 | 0.6571          | 0.82     |
+| 0.2888        | 18.0  | 2034 | 0.6880          | 0.81     |
+| 0.1605        | 19.0  | 2147 | 0.6874          | 0.82     |
+| 0.1492        | 20.0  | 2260 | 0.6711          | 0.82     |
 
 
 ### Framework versions