update model card README.md

README.md

@@ -16,13 +16,13 @@ model-index:
     dataset:
       name: GTZAN
       type: marsyas/gtzan
-      config: default
+      config: all
       split: train
-      args: default
+      args: all
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.85
+      value: 0.89
 ---
 
 <!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6936
-- Accuracy: 0.85
+- Loss: 0.5167
+- Accuracy: 0.89
 
 ## Model description
 
@@ -59,27 +59,29 @@ 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: 12
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.1495        | 1.0   | 113  | 1.0290          | 0.69     |
-| 0.8804        | 2.0   | 226  | 0.7815          | 0.74     |
-| 0.6108        | 3.0   | 339  | 0.6531          | 0.79     |
-| 0.5577        | 4.0   | 452  | 0.6071          | 0.81     |
-| 0.6466        | 5.0   | 565  | 0.5756          | 0.81     |
-| 0.2837        | 6.0   | 678  | 0.6321          | 0.81     |
-| 0.2539        | 7.0   | 791  | 0.6233          | 0.83     |
-| 0.027         | 8.0   | 904  | 0.6481          | 0.83     |
-| 0.0469        | 9.0   | 1017 | 0.6713          | 0.84     |
-| 0.0242        | 10.0  | 1130 | 0.6936          | 0.85     |
+| 2.2163        | 1.0   | 113  | 2.0720          | 0.34     |
+| 1.7237        | 2.0   | 226  | 1.5361          | 0.59     |
+| 1.3254        | 3.0   | 339  | 1.2044          | 0.65     |
+| 1.0757        | 4.0   | 452  | 1.0578          | 0.66     |
+| 1.0683        | 5.0   | 565  | 0.8947          | 0.78     |
+| 0.9307        | 6.0   | 678  | 0.7716          | 0.82     |
+| 1.0313        | 7.0   | 791  | 0.7210          | 0.82     |
+| 0.6988        | 8.0   | 904  | 0.6506          | 0.8      |
+| 0.8053        | 9.0   | 1017 | 0.5944          | 0.81     |
+| 0.6243        | 10.0  | 1130 | 0.5637          | 0.87     |
+| 0.6238        | 11.0  | 1243 | 0.5212          | 0.89     |
+| 0.4493        | 12.0  | 1356 | 0.5167          | 0.89     |
 
 
 ### Framework versions
 
-- Transformers 4.31.0
+- Transformers 4.32.0.dev0
 - Pytorch 2.0.1+cu118
-- Datasets 2.14.1
+- Datasets 2.14.2
 - Tokenizers 0.13.3