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 [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: nan
-- Accuracy: 0.1
+- Loss: 0.9220
+- Accuracy: 0.73
 
 ## Model description
 
@@ -38,39 +38,31 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8e-05
+- learning_rate: 7e-05
 - train_batch_size: 2
 - eval_batch_size: 2
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 8
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 18
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.2369        | 1.0   | 112  | 2.1698          | 0.32     |
-| 1.9093        | 2.0   | 225  | 1.7851          | 0.34     |
-| 1.5339        | 3.0   | 337  | 1.4068          | 0.46     |
-| 1.4127        | 4.0   | 450  | 1.2916          | 0.53     |
-| 0.991         | 5.0   | 562  | 1.0534          | 0.58     |
-| 0.8365        | 6.0   | 675  | 0.9250          | 0.67     |
-| 0.6994        | 7.0   | 787  | 1.0032          | 0.72     |
-| 1.3372        | 8.0   | 900  | nan             | 0.41     |
-| 4.3377        | 9.0   | 1012 | nan             | 0.29     |
-| 0.0           | 10.0  | 1125 | nan             | 0.1      |
-| 0.0           | 11.0  | 1237 | nan             | 0.1      |
-| 0.0           | 12.0  | 1350 | nan             | 0.1      |
-| 0.0           | 13.0  | 1462 | nan             | 0.1      |
-| 0.0           | 14.0  | 1575 | nan             | 0.1      |
-| 0.0           | 15.0  | 1687 | nan             | 0.1      |
-| 0.0           | 16.0  | 1800 | nan             | 0.1      |
-| 0.0           | 17.0  | 1912 | nan             | 0.1      |
-| 0.0           | 17.92 | 2016 | nan             | 0.1      |
+| 2.2456        | 1.0   | 56   | 2.2312          | 0.34     |
+| 2.059         | 1.99  | 112  | 1.9662          | 0.32     |
+| 1.8574        | 2.99  | 168  | 1.6258          | 0.5      |
+| 1.4447        | 4.0   | 225  | 1.4547          | 0.59     |
+| 1.4224        | 5.0   | 281  | 1.2372          | 0.65     |
+| 1.2131        | 5.99  | 337  | 1.0879          | 0.67     |
+| 1.1151        | 6.99  | 393  | 1.0599          | 0.69     |
+| 0.9471        | 8.0   | 450  | 1.0339          | 0.68     |
+| 1.0319        | 9.0   | 506  | 0.9568          | 0.71     |
+| 0.9313        | 9.96  | 560  | 0.9220          | 0.73     |
 
 
 ### Framework versions