End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - marsyas/gtzan
+metrics:
+- accuracy
 model-index:
 - name: distilhubert-finetuned-gtzan
-  results: []
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.86
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
 # distilhubert-finetuned-gtzan
 
 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: 0.5324
+- Accuracy: 0.86
 
 ## Model description
 
@@ -44,6 +62,22 @@ The following hyperparameters were used during training:
 - num_epochs: 10
 - mixed_precision_training: Native AMP
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9201        | 1.0   | 113  | 1.8096          | 0.56     |
+| 1.2331        | 2.0   | 226  | 1.2709          | 0.6      |
+| 1.0386        | 3.0   | 339  | 0.9960          | 0.73     |
+| 0.6721        | 4.0   | 452  | 0.8535          | 0.72     |
+| 0.5598        | 5.0   | 565  | 0.7156          | 0.81     |
+| 0.4382        | 6.0   | 678  | 0.6253          | 0.83     |
+| 0.2701        | 7.0   | 791  | 0.5411          | 0.84     |
+| 0.1164        | 8.0   | 904  | 0.5460          | 0.83     |
+| 0.1872        | 9.0   | 1017 | 0.5464          | 0.84     |
+| 0.0898        | 10.0  | 1130 | 0.5324          | 0.86     |
+
+
 ### Framework versions
 
 - Transformers 4.41.2