update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.86
+      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 [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5051
-- Accuracy: 0.86
+- Loss: 0.5086
+- Accuracy: 0.88
 
 ## Model description
 
@@ -55,7 +55,7 @@ The following hyperparameters were used during training:
 - learning_rate: 5e-05
 - train_batch_size: 2
 - eval_batch_size: 2
-- seed: 42
+- seed: 14
 - gradient_accumulation_steps: 4
 - total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -67,26 +67,26 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.8767        | 1.0   | 112  | 0.6930          | 0.78     |
-| 0.5251        | 2.0   | 225  | 0.5514          | 0.82     |
-| 0.5388        | 3.0   | 337  | 0.5380          | 0.81     |
-| 0.1679        | 4.0   | 450  | 0.3927          | 0.9      |
-| 0.0227        | 5.0   | 562  | 0.5077          | 0.87     |
-| 0.0012        | 6.0   | 675  | 0.5441          | 0.88     |
-| 0.0472        | 7.0   | 787  | 0.7029          | 0.86     |
-| 0.0015        | 8.0   | 900  | 0.5576          | 0.84     |
-| 0.0095        | 9.0   | 1012 | 0.6228          | 0.85     |
-| 0.0002        | 10.0  | 1125 | 0.4116          | 0.88     |
-| 0.0001        | 11.0  | 1237 | 0.7136          | 0.82     |
-| 0.0001        | 12.0  | 1350 | 0.4885          | 0.88     |
-| 0.0001        | 13.0  | 1462 | 0.4831          | 0.87     |
-| 0.0001        | 14.0  | 1575 | 0.4606          | 0.87     |
-| 0.0           | 15.0  | 1687 | 0.4930          | 0.87     |
-| 0.0           | 16.0  | 1800 | 0.4937          | 0.87     |
-| 0.0           | 17.0  | 1912 | 0.4974          | 0.86     |
-| 0.0           | 18.0  | 2025 | 0.4989          | 0.86     |
-| 0.0           | 19.0  | 2137 | 0.5060          | 0.86     |
-| 0.0           | 19.91 | 2240 | 0.5051          | 0.86     |
+| 0.5982        | 1.0   | 112  | 0.5195          | 0.83     |
+| 0.3962        | 2.0   | 225  | 0.5597          | 0.81     |
+| 0.3143        | 3.0   | 337  | 0.7567          | 0.83     |
+| 0.0548        | 4.0   | 450  | 0.5270          | 0.86     |
+| 0.0119        | 5.0   | 562  | 0.5813          | 0.88     |
+| 0.2503        | 6.0   | 675  | 0.7523          | 0.86     |
+| 0.0008        | 7.0   | 787  | 0.6239          | 0.85     |
+| 0.0003        | 8.0   | 900  | 0.4949          | 0.9      |
+| 0.0001        | 9.0   | 1012 | 0.5706          | 0.88     |
+| 0.0003        | 10.0  | 1125 | 0.4898          | 0.92     |
+| 0.0001        | 11.0  | 1237 | 0.5281          | 0.89     |
+| 0.0001        | 12.0  | 1350 | 0.5197          | 0.88     |
+| 0.0002        | 13.0  | 1462 | 0.5036          | 0.9      |
+| 0.0           | 14.0  | 1575 | 0.5362          | 0.9      |
+| 0.0           | 15.0  | 1687 | 0.5065          | 0.89     |
+| 0.0           | 16.0  | 1800 | 0.5011          | 0.9      |
+| 0.0           | 17.0  | 1912 | 0.5025          | 0.88     |
+| 0.0           | 18.0  | 2025 | 0.5027          | 0.88     |
+| 0.0           | 19.0  | 2137 | 0.5074          | 0.88     |
+| 0.0           | 19.91 | 2240 | 0.5086          | 0.88     |
 
 
 ### Framework versions