update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.84
+      value: 0.88
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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: 0.5915
-- Accuracy: 0.84
+- Loss: 0.6645
+- Accuracy: 0.88
 
 ## Model description
 
@@ -53,30 +53,50 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
-- gradient_accumulation_steps: 2
-- 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: 10
+- num_epochs: 30
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9842        | 1.0   | 112  | 1.8316          | 0.3      |
-| 1.5556        | 2.0   | 225  | 1.4607          | 0.51     |
-| 1.1784        | 3.0   | 337  | 1.2548          | 0.52     |
-| 0.8821        | 4.0   | 450  | 1.1416          | 0.61     |
-| 0.9141        | 5.0   | 562  | 1.0491          | 0.64     |
-| 0.7517        | 6.0   | 675  | 0.8565          | 0.73     |
-| 0.7526        | 7.0   | 787  | 0.7474          | 0.78     |
-| 0.3974        | 8.0   | 900  | 0.7273          | 0.78     |
-| 0.444         | 9.0   | 1012 | 0.5932          | 0.84     |
-| 0.6686        | 9.96  | 1120 | 0.5915          | 0.84     |
+| 2.2685        | 1.0   | 56   | 2.2069          | 0.44     |
+| 2.0208        | 1.99  | 112  | 1.8352          | 0.46     |
+| 1.7603        | 2.99  | 168  | 1.5275          | 0.49     |
+| 1.4843        | 4.0   | 225  | 1.4296          | 0.52     |
+| 1.347         | 5.0   | 281  | 1.2222          | 0.52     |
+| 1.2364        | 5.99  | 337  | 1.1477          | 0.62     |
+| 1.2082        | 6.99  | 393  | 1.0181          | 0.67     |
+| 0.9861        | 8.0   | 450  | 0.9598          | 0.71     |
+| 0.752         | 9.0   | 506  | 0.7499          | 0.77     |
+| 1.006         | 9.99  | 562  | 0.8190          | 0.79     |
+| 0.6725        | 10.99 | 618  | 0.8798          | 0.75     |
+| 0.7457        | 12.0  | 675  | 0.6276          | 0.81     |
+| 0.4605        | 13.0  | 731  | 0.6086          | 0.85     |
+| 0.5751        | 13.99 | 787  | 0.6894          | 0.75     |
+| 0.4886        | 14.99 | 843  | 0.6109          | 0.83     |
+| 0.2429        | 16.0  | 900  | 0.6076          | 0.85     |
+| 0.3084        | 17.0  | 956  | 0.4646          | 0.86     |
+| 0.3762        | 17.99 | 1012 | 0.8349          | 0.81     |
+| 0.2897        | 18.99 | 1068 | 0.4509          | 0.89     |
+| 0.1296        | 20.0  | 1125 | 0.6791          | 0.86     |
+| 0.1291        | 21.0  | 1181 | 0.6466          | 0.85     |
+| 0.3784        | 21.99 | 1237 | 0.6272          | 0.88     |
+| 0.1156        | 22.99 | 1293 | 0.7916          | 0.85     |
+| 0.2093        | 24.0  | 1350 | 0.6536          | 0.85     |
+| 0.2167        | 25.0  | 1406 | 0.7050          | 0.87     |
+| 0.1095        | 25.99 | 1462 | 0.6128          | 0.88     |
+| 0.1004        | 26.99 | 1518 | 0.6092          | 0.89     |
+| 0.0897        | 28.0  | 1575 | 0.6730          | 0.88     |
+| 0.083         | 29.0  | 1631 | 0.6396          | 0.89     |
+| 0.0343        | 29.87 | 1680 | 0.6645          | 0.88     |
 
 
 ### Framework versions