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: 0.5863
-- Accuracy: 0.81
+- Loss: 0.9594
+- Accuracy: 0.83
 
 ## Model description
 
@@ -38,30 +38,40 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 8e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - 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: 10
+- num_epochs: 20
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7494        | 1.0   | 113  | 1.8125          | 0.47     |
-| 1.2377        | 2.0   | 226  | 1.2643          | 0.69     |
-| 1.0113        | 3.0   | 339  | 0.9183          | 0.73     |
-| 0.701         | 4.0   | 452  | 0.7757          | 0.8      |
-| 0.4447        | 5.0   | 565  | 0.7241          | 0.82     |
-| 0.295         | 6.0   | 678  | 0.5659          | 0.81     |
-| 0.2375        | 7.0   | 791  | 0.5854          | 0.79     |
-| 0.2417        | 8.0   | 904  | 0.5610          | 0.83     |
-| 0.1838        | 9.0   | 1017 | 0.5412          | 0.8      |
-| 0.4115        | 10.0  | 1130 | 0.5863          | 0.81     |
+| 1.874         | 1.0   | 113  | 1.8949          | 0.42     |
+| 1.2872        | 2.0   | 226  | 1.3293          | 0.57     |
+| 0.9764        | 3.0   | 339  | 0.9030          | 0.72     |
+| 0.5805        | 4.0   | 452  | 0.6561          | 0.83     |
+| 0.4618        | 5.0   | 565  | 0.5127          | 0.87     |
+| 0.1487        | 6.0   | 678  | 0.7336          | 0.77     |
+| 0.1542        | 7.0   | 791  | 0.5496          | 0.84     |
+| 0.267         | 8.0   | 904  | 0.6534          | 0.85     |
+| 0.037         | 9.0   | 1017 | 0.7327          | 0.85     |
+| 0.0089        | 10.0  | 1130 | 1.1979          | 0.76     |
+| 0.0436        | 11.0  | 1243 | 1.0857          | 0.82     |
+| 0.003         | 12.0  | 1356 | 0.9266          | 0.84     |
+| 0.0019        | 13.0  | 1469 | 0.9791          | 0.84     |
+| 0.0017        | 14.0  | 1582 | 0.9259          | 0.84     |
+| 0.0015        | 15.0  | 1695 | 0.9836          | 0.83     |
+| 0.0014        | 16.0  | 1808 | 1.0018          | 0.83     |
+| 0.0013        | 17.0  | 1921 | 0.9896          | 0.83     |
+| 0.0012        | 18.0  | 2034 | 0.9836          | 0.84     |
+| 0.0012        | 19.0  | 2147 | 0.9759          | 0.84     |
+| 0.0011        | 20.0  | 2260 | 0.9594          | 0.83     |
 
 
 ### Framework versions