update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.85
+      value: 0.84
 ---
 
 <!-- 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 [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5673
-- Accuracy: 0.85
+- Loss: 0.6527
+- Accuracy: 0.84
 
 ## Model description
 
@@ -60,22 +60,27 @@ 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: 15
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0215        | 1.0   | 112  | 1.9334          | 0.2      |
-| 1.5799        | 2.0   | 225  | 1.3860          | 0.58     |
-| 1.1392        | 3.0   | 337  | 1.2514          | 0.55     |
-| 0.9529        | 4.0   | 450  | 0.9821          | 0.65     |
-| 0.7872        | 5.0   | 562  | 0.8525          | 0.74     |
-| 0.7504        | 6.0   | 675  | 0.9070          | 0.71     |
-| 0.8104        | 7.0   | 787  | 0.5771          | 0.83     |
-| 0.303         | 8.0   | 900  | 0.6943          | 0.81     |
-| 0.3939        | 9.0   | 1012 | 0.6368          | 0.84     |
-| 0.6499        | 9.96  | 1120 | 0.5673          | 0.85     |
+| 2.1249        | 1.0   | 112  | 1.9377          | 0.43     |
+| 1.6556        | 2.0   | 225  | 1.5867          | 0.47     |
+| 1.2564        | 3.0   | 337  | 1.2670          | 0.56     |
+| 1.0786        | 4.0   | 450  | 1.1080          | 0.59     |
+| 0.895         | 5.0   | 562  | 0.8518          | 0.75     |
+| 0.7177        | 6.0   | 675  | 1.0047          | 0.7      |
+| 0.964         | 7.0   | 787  | 0.7430          | 0.75     |
+| 0.4107        | 8.0   | 900  | 1.0347          | 0.71     |
+| 0.4166        | 9.0   | 1012 | 0.5399          | 0.85     |
+| 0.1234        | 10.0  | 1125 | 0.6266          | 0.83     |
+| 0.0902        | 11.0  | 1237 | 0.6292          | 0.84     |
+| 0.1211        | 12.0  | 1350 | 0.7393          | 0.84     |
+| 0.4082        | 13.0  | 1462 | 0.6524          | 0.85     |
+| 0.3442        | 14.0  | 1575 | 0.5732          | 0.86     |
+| 0.0913        | 14.93 | 1680 | 0.6527          | 0.84     |
 
 
 ### Framework versions